Infosys

Product Manager

• Shape AI use cases — identify where machine learning, generative AI and agentic AI can solve real business problems, and equally where they cannot
• Frame business cases and value hypotheses for AI products, including success metrics for probabilistic systems and the realistic costs, risks and dependencies
• Own and prioritise the AI product backlog, translating ambiguous opportunities into well-scoped, testable increments that data science and engineering teams can deliver
• Define product vision and roadmaps for AI-enabled products, balancing experimentation with production-grade delivery
• Translate business problems into AI problems — specify data requirements, evaluation criteria, acceptance criteria and guardrails for ML and GenAI features
• Advise on Responsible AI in everyday product decisions — fairness, transparency, accountability, human oversight and proportionate risk management
• Guide AI products across the full lifecycle: ideation, data readiness, prototyping, evaluation, deployment, monitoring and continuous improvement
• Engage business stakeholders, subject matter experts and end users to validate problems, test prototypes and drive adoption
• Collaborate with distributed delivery teams, including offshore, to ensure quality and pace
• Contribute to Infosys Consulting’s thought leadership, accelerators and reusable assets for AI Product Management

AI Product Owner – Consultant

Consultant

• Collaborate with client counterparts to define long-term vision, goals, and strategies.
• Contribute to the design and development of client future processes and organizations with corresponding transformation roadmaps.
• Conduct requirements workshops with a team of global IT professional & subject matter experts, translating those requirements into actionable project initiatives w/associated metrics.
• Solution targeted processes, leveraging best practices.
• Solution and document functional specifications.
• Define, execute, and support testing of the solution.
• Perform knowledge transfer to client and supporting organizations throughout all phases of the project.
• Support management of project execution from start-to-finish to deliver according to plan (scope, quality, and time).
• Coach and develop team members to deliver quality results and promote professional development.
• Mentor and coach team members through formal, performance evaluation methods and informal, individual feedback opportunities.
• Collaborate and share knowledge.
• Contribute to practice growth through recruitment, training, and retention.
• Provide insight and thought leadership to develop innovative assets, including differentiated points of view and methodologies.
• Provide insights on new and emerging best practices across Capital Markets industry and contribute to the development of service offerings.
• Prepare thought papers and participate in industry conferences and forums.
• Build social networks that enable knowledge and information flow and stay abreast of developments in Capital markets and financial advisory expertise areas.
• Drive integration of EDM with upstream and downstream systems.
• Design and oversee data workflows across reference, market, product, and trade data domains.
• Guide implementation of data integration and processing layers (batch and real-time).
• Define and enforce data governance, stewardship, and lineage practices to ensure traceability, auditability, and compliance.
• Drive performance tuning, system testing (unit → integration → UAT → parallel), and deployment to production environments ensuring operational readiness.
• Mentor junior EDM consultants and contribute to implementation best practices, continuous improvement, and product roadmap feedback.
• Collaborate with other streams including technology delivery streams across Infosys to deliver a compelling value proposition to the client.
• Manage and minimize engagement risk by proactively identifying issues and recommended courses of remediation.
• Build client relationships towards expanding the footprint within the client organization.

Enterprise Data Management Consultant – Principal Level

Operations

• Advise clients on designing, evolving, and operating modern IT and Digital operating models in response to AI adoption, cloud transformation, cyber resilience, and complex service ecosystems.
• Lead or contribute to proposals and engagements focused on IT and AI Operating Model strategy and design, including the definition of roles, decision rights, governance, service accountability, and performance metrics.
• Focus on transitioning towards AI-enabled and agent-supported operating environments.
• Lead project teams to deliver current-state assessments, target operating model (TOM) design, and implementation of ITSM and SIAM governance, principles, and operating processes.
• Ensure effective integration into existing service delivery environments.

Digital Operations Consultant

• Provide expert advisory support to organisations seeking to optimise IT service delivery and digital operations
• Design and implement Target Operating Models (TOMs) aligned to AI, Cloud, Cyber and Service Management strategies
• Advise and guide the design and implementation of Service Integration & Management (SIAM) models in multi-vendor and delivery function environments
• Support organisations moving towards AI-enabled operations, ensuring AI governance aligns with enterprise-wide controls and risk frameworks
• Analyse current IT organisational design, operating models, and ITSM processes to identify improvement opportunities
• Develop practical, execution-ready transformation roadmaps
• Contribute to and lead the development of consulting offerings and thought leadership
• Govern and manage the execution of operating model and service management transformations
• Establish performance metrics and success measures to drive continuous improvement
• Work confidently across Agile, product-centric, and traditional SDLC delivery models
• Lead senior client conversations and articulate the value of IT and Digital Operations to the business
• Experience working with ITSM tools and platforms (e.g. ServiceNow) and advising on tool selection

• Following our recent communication on the launch of the IC StepUp Policy, we are pleased to announce that we are now opening tthe below senior consultant role under this program.
• Work independently to translate business requirements into **user stories** and acceptance criteria within an agile framework.
• Ensure requirements are clear, complete, and aligned with business objectives.
• Support integration activities between the new vendor platform, internal systems, and external systems.
• Collaborate with technical teams to validate feasibility and ensure smooth implementation.
• Build strong relationships with **product owners, business owners, SMEs, and vendors**.
• Facilitate workshops and discussions to align priorities and resolve conflicts.
• Navigate ambiguity and drive clarity in requirements and solution design.
• Challenge assumptions respectfully and influence decisions when direction needs reconsideration.
• Actively participate in sprint planning, backlog refinement, and daily stand-ups.
• Ensure deliverables meet quality standards and timelines.

Senior Consultant

Engineer

• Support the testing, validation, operational assessment, and field enablement of agentic AI workflows deployed across tactical and operational environments.
• Validate AI-enabled workflows, ensuring operational reliability, supporting user acceptance activities, and enabling end users to effectively operate AI-assisted tools.
• Build and maintain end-to-end validation plans and operational test strategies for agentic AI workflows.
• Develop and execute regression test suites supporting prompt updates and model changes.
• Capture, organize, and maintain validation evidence, test results, issue tracking, and supporting artifacts for customer review.

Workflow Validation – Field Enablement Engineer

Solutions Engineer

• Build and maintain MCP servers and integration services that expose operational applications, mission systems, device controls, sensor data, databases, file systems, and enterprise services to agentic AI workflows and operational applications.
• Support integrations with high-side and mission-relevant data environments, including operational repositories, analytics platforms, and mission databases such as Arsenal and other classified or restricted-access systems.
• Implement integrations for the X9 Spider Mission Computer architecture, including onboard compute environments, hardware interfaces, sensor integrations, communications systems, and mission-specific peripherals.
• Integrate operational AI and mission workflows with EMSCO, Lattice, AIDP, and related mission systems to support interoperability within the broader NGC2 architecture and operational ecosystem.
• Integrate agents with external command systems, reporting tools, operational platforms, and mission applications through MCP services, APIs, adapters, and middleware solutions.
• Implement secure tool interfaces with clearly defined schemas, permission boundaries, authentication controls, audit logging, input validation, error handling, and operational safeguards.
• Implement read/write separation and execution controls that allow agents to inspect system state, validate operational context, and safely execute authorized actions.
• Develop and execute automated integration and validation testing for MCP services and operational tool interfaces, including parameter validation, workflow testing, tool-call verification, failure-state testing, and operational edge-case evaluation.
• Support deployment, sustainment, troubleshooting, and optimization of MCP services and integration pipelines across cloud, edge, tactical, and disconnected operational environments.
• Collaborate with AI engineers, software developers, systems engineers, cybersecurity teams, and operational stakeholders to ensure integrations align with mission requirements, security constraints, and operational workflows.
• Train customer technical personnel on MCP service architecture, deployment workflows, testing methodologies, troubleshooting procedures, and safe extension of MCP-enabled capabilities within operational environments such as X9 Spider.
• Maintain technical documentation, interface control documents (ICDs), API references, deployment procedures, sample tool calls, configuration guides, and operational integration notes supporting customer sustainment and future enhancements.
• Support DevSecOps and CI/CD activities related to integration, testing, accreditation, and deployment of operational software and AI-enabled services.

MCP/Integration Engineer

Artificial Intelligence

• Evaluate candidate Large Language Models (LLMs), embedding models, and AI inference solutions for quality, latency, memory utilization, reliability, and operational performance on embedded GPU-enabled edge compute platforms, including the X9 Spider Mission Computer architecture.
• Tune and optimize AI model runtime configurations for edge deployment, including quantization strategies, batching configurations, context window sizing, cache behavior, inference scheduling, and GPU memory utilization specific to operational edge hardware environments.
• Collaborate with customer stakeholders to assess mission requirements and evaluate alternative edge compute platforms when operational demands exceed X9 Spider capabilities or when cost, performance, power, size, weight, or thermal tradeoffs require additional analysis.
• Benchmark agentic AI workflows, inference pipelines, and model-serving architectures against target hardware constraints and operational performance thresholds.
• Recommend model-selection, runtime, and configuration tradeoffs balancing mission effectiveness, latency, throughput, resource utilization, reliability, and operational sustainability.
• Build and maintain repeatable performance and stress-testing frameworks for evaluating latency, throughput, tool-call overhead, failover behavior, degraded-resource conditions, and disconnected operational scenarios on edge compute platforms.
• Package, deploy, validate, and sustain local model-serving components and inference services to support reliable operation within tactical and edge environments.
• Collaborate with agent engineers, AI developers, and integration teams to validate that agent behavior, workflow reliability, and operational outcomes remain acceptable following model compression, quantization, runtime optimization, or hardware configuration changes.
• Support deployment, troubleshooting, optimization, and sustainment activities for AI-enabled applications operating in edge, airborne, tactical, or disconnected operational environments.
• Train customer technical personnel on supported model profiles, operational constraints, runtime tuning considerations, deployment limitations, troubleshooting procedures, and platform sustainment best practices.
• Maintain technical documentation, benchmarking results, model validation reports, deployment procedures, optimization baselines, configuration guides, and operational support materials.
• Support DevSecOps and CI/CD activities associated with AI model packaging, deployment automation, runtime validation, and operational release processes.

Edge AI – Model Optimization Engineer

AI Engineer

• Partner with customer SMEs and operational stakeholders to translate mission workflows and operational requirements into agentic AI solutions, including intelligent agents, workflow specialists, guardrails, tools, and validation frameworks.
• Design, develop, and maintain agent definitions and configurations, including objectives, behavioral instructions, input/output contracts, safety policies, operational constraints, and tool utilization rules.
• Develop workflow-specific AI specialists and reusable agent patterns to support operational and enterprise use cases while maintaining clear functional boundaries and scalable architectures.
• Build and maintain comprehensive AI testing and evaluation suites, including gold-standard input/output validation, adversarial testing, guardrail validation, scope-boundary testing, tool-use validation, regression testing, and multi-turn conversational testing.
• Analyze failed, degraded, or stale agent test results to identify performance gaps, tune agent behavior, improve reliability, and document updates across agent versions and releases.
• Integrate AI agents, orchestration workflows, APIs, and supporting services into existing application and operational environments using modern software engineering and DevSecOps practices.
• Support the deployment, sustainment, troubleshooting, and optimization of AI-enabled applications and agentic workflows across cloud, edge, and hybrid environments.
• Train and mentor customer agent creators on Agent Builder workflows, publishing processes, testing methodologies, maintenance procedures, and operational best practices.
• Develop reusable templates, workflow examples, implementation guides, and best-practice documentation to enable scalable and consistent customer development of agentic AI solutions.
• Collaborate with cross-functional engineering, operations, cybersecurity, and product teams to ensure AI-enabled capabilities align with mission objectives, security requirements, and operational constraints.
• Contribute to continuous improvement efforts for AI-enabled applications, orchestration frameworks, testing methodologies, and software delivery pipelines.

Application/Agentic AI Engineer

LLM Engineer

• Research, design, develop, and deploy innovative AI/ML and Generative AI solutions across various mission-focused problem sets
• Support development of advanced AI capabilities using technologies such as large language models and cloud-native AI services including AWS Bedrock
• Participate in all phases of the software engineering lifecycle, including research, requirements analysis, solution design, model development, integration, deployment, evaluation, and testing

Generative AI Engineer

• Gather and analyze client PLM requirements and processes.
• Design and implement PLM solutions aligned with client objectives, including workflow design, data management, and integration with ERP/CRM systems.
• Configure and implement PLM systems (Siemens Teamcenter, PTC Windchill, Dassault ENOVIA, SAP PLM).
• Assist in creating PLM roadmaps, governance models, and best practices for clients.
• Support data migration, integration, testing, and user training.
• Recommend PLM best practices and process improvements.
• Collaborate with cross-functional teams to ensure successful project delivery.

Junior PLM Consultant

Business Analyst

• Act as primary Point of Contact (POC) for all Program inquiries, financial matters, and administrative support
• Program Operational Support: Assist on memorandums, policy and Standard Operating Procedures (SOP) at the direction of the Chief Inspector AWS III
• Compile weekly and annual statistics related to the video program
• Assemble necessary documentation for submission to the Training Division for video related training programs
• Oversee and manage the Program Request Tracker, ensuring accurate tracking and timely updates
• Assist Chief Inspector AWS III with electronic records management using agency-specific software, ensuring proper organization and compliance
• Gather, identify, and analyze information derived from Law Enforcement databases to generate operational and intelligence reports as needed
• Maintain and monitor AWS Spectrum funding; ensure funds are used in accordance with AWS III Spectrum Auction guidance
• Input and reconcile financial transactions into United Financial Management System (UFMS)
• Prepare and generate financial status reports, ensuring accuracy and timely delivery
• Prepare requisition documents for procurement of supplies, service and equipment
• Verify payments sent via the Invoice Processing Platform (IPP); research and resolve problems with invoices and ensure proper payment
• Review all vendor invoices for accuracy; POC for invoices in dispute
• Request signatures on AWS III and other USMS invoices
• Responsible for the proper retention or disposal of equipment for excess
• Prepare property reports for current and annual inventory inspections
• Other intelligence and technical duties as assigned by the Chief Inspector AWS III

Program Management Analyst

• Lead and manage large-scale cloud transformation programmes from initiation through to delivery and transition to operations
• Own programme-level planning, governance, risk management, financial oversight, and delivery assurance
• Coordinate multi-stream delivery across architecture, platform, application, security, and operations teams
• Manage senior client stakeholders, providing clear status reporting, issue management, and decision support
• Oversee cloud migration and modernisation initiatives, ensuring alignment to agreed scope, timelines, and outcomes
• Establish and run programme governance forums, Risks, Assumptions, Issues, Dependencies (RAID) management, and executive reporting
• Ensure delivery adheres to cloud best practices, regulatory constraints, and organisational standards
• Contribute to proposals, programme planning, and transformation offerings within the Cloud & Infrastructure capability

Senior Consultant – Cloud Transformation Manager, German Speaking

Cloud Engineer

• **About Your Role**
• As a Cloud Architect within our Cloud & Infrastructure capability, you will lead and govern the migration, transformation and design of secure, scalable, and cost-efficient cloud platforms across AWS, Azure, and Google Cloud. You will set architectural direction and act as design authority for cloud-first, hybrid, and multi-cloud strategies aligned to business outcomes, regulatory requirements, and digital sovereignty considerations.
• You will define enterprise-scale, cloud-native and AI-ready architectures supporting application platforms, data and AI workloads, and GenAI-enabled use cases. Working across strategy, target architectures, and delivery programmes, you will ensure solutions are resilient, secure, and operationally robust from design through implementation.
• You will lead and assure architecture design across cloud landing zones, platform engineering, observability, cloud security, and cloud economics, working closely with senior client stakeholders, delivery leadership, hyperscaler partners, and Infosys Consulting specialists.
• **Key Responsibilities & Capabilities**
• - Lead cloud transformation initiatives, including migration assessments, discovery activities, and definition of target cloud architectures
• - Define and govern enterprise cloud architecture standards and reference architecture across AWS, Azure, and/or Google Cloud
• - Act as design authority for complex cloud, hybrid, and multi-cloud initiatives
• - Lead the design of AI-ready and GenAI-enabled cloud architectures, including secure data platforms and scalable inference patterns
• - Own cloud transformation assessments, defining target architectures, migration strategies, and phased roadmaps
• - Apply and enforce Well-Architected, security-by-design, and cost-optimisation principles
• - Engage confidently with senior client stakeholders, clearly articulating architectural options and trade-offs
• - Contribute to proposals, offerings, and thought leadership within the Cloud & Infrastructure capability

Senior Consultant – Cloud Architect, German Speaking

• Define and lead enterprise FinOps strategies across public cloud environments (AWS, Azure, and/or Google Cloud)
• Advise senior technology, finance, and business stakeholders on cloud cost governance and value optimisation
• Design and implement FinOps operating models, including chargeback/showback, budgeting, forecasting, and cost allocation
• Establish KPIs, dashboards, and reporting to provide transparency into cloud spend, efficiency, and business value
• Lead optimisation initiatives including rightsizing, rate optimisation, commitment management, and workload efficiency
• Embed cost-aware practices into architecture, platform, and engineering design decisions
• Support large-scale cloud migrations and modernisation programmes from a financial and value perspective
• Contribute to proposals, client engagements, and offerings within the Cloud & Infrastructure capability

AI Product Owner – Consultant

Enterprise Data Management Consultant – Principal Level

Digital Operations Consultant

Digital Operations Consultant

Senior Consultant

Workflow Validation – Field Enablement Engineer

MCP/Integration Engineer

Edge AI – Model Optimization Engineer

Application/Agentic AI Engineer

Generative AI Engineer

Junior PLM Consultant

Program Management Analyst

Senior Consultant – Cloud Transformation Manager, German Speaking

Senior Consultant – Cloud Architect, German Speaking

Senior FinOps Consultant – German Speaking