Artificial Intelligence

• Drive AI-powered innovation initiatives to enhance software testing quality, efficiency, coverage, and speed.
• Design and develop enterprise-scale automation frameworks using Playwright, SpecFlow, AI Agents, and Generative AI technologies.
• Build intelligent solutions capable of automatically generating, maintaining, and optimising test scripts through AI.
• Architect and implement Agentic AI frameworks, autonomous testing workflows, and MCP Server-based integrations.
• Develop AI-powered testing assistants using Microsoft Copilot, Copilot Studio, LLMs, and AI Agents.
• Collaborate with Product, AI Engineering, and Automation COE teams to define and enhance AI-driven testing capabilities and roadmap initiatives.
• Work closely with enterprise customers to identify testing challenges and drive AI-led Quality Engineering transformation programmes.
• Develop Proof of Concepts (POCs), innovation accelerators, and reusable frameworks demonstrating measurable business value through AI-powered testing.
• Define enterprise test automation strategies, architecture standards, and best practices while mentoring engineering and automation teams.
• Support customer workshops, solution consulting, pre-sales engagements, demonstrations, and executive presentations while staying abreast of emerging AI and automation technologies.

AI Automation Consultant

• Engage internal SMEs to understand current processes and as-is workflows — translate into buildable AI requirements.
• Demo working solutions to internal stakeholders up to business leadership level.
• Support the Architect during feasibility and POC phases — contribute to rapid builds and validate fit.
• Maintain stakeholder communication throughout: progress updates, issue escalation, solution walkthroughs.
• Co-invest with the Architect in upfront solution design — design robustness directly determines build speed and test quality.
• Translate architecture into implementation plans — break down into assignable streams for Developer and Associate.
• Own day-to-day technical decisions during build when the Architect is focused on other projects.
• Identify architectural risks early and escalate before they become build or production problems.
• Build complex solution components end-to-end on AWS AgentCore and LangGraph — hands-on coding role.
• Scale solutions from POC to production: performance, reliability, monitoring, and cost management.
• Debug production failures: hallucination patterns, retrieval degradation, agent loops, latency regressions.
• Use AI coding tools (Claude Code, GitHub Copilot, Cursor, Cline) to accelerate delivery.
• Own all generated code.
• Build Low Code automations (Copilot Studio, Power Automate) when use case and bandwidth allow.
• Guide Developer and Associate through implementation, code reviews, and debugging.
• Ensure the team uses AI tools effectively — accelerating delivery without sacrificing code understanding.

Automation and AI Solutions Lead

• Design and deploy intelligent automation and agentic AI solutions that save time, slash errors, and WOW stakeholders.
• Collaborate on AI strategies, ensuring our clients’ critical needs are met.
• Blend tech prowess with domain insights — think big, fail fast, innovate.
• Evangelize best practices in this thrilling fusion of AI and business.

Agentic AI, GEN AI

• Annotation - Audio/Video/Image/Sentence/Word validation.
• Categorization, Conversational interactions.
• Content creation.
• Correction.
• Evaluation.
• Localization.

Indian English Linguistic Project

• Help shape the future of intelligent engineering and power plant operations by developing hands-on AI/ML and agent-based solutions
• Build intelligent tools and AI agents that automate control logic generation, graphics configuration, reporting, and engineering workflows
• Analyze control system and operational data to uncover patterns, develop predictive capabilities, and deliver data-driven decision support for real-world power plant environments
• Apply AI-based anomaly detection, diagnostics, and decision-support solutions to real power-plant operational challenges
• Translate plant operating behavior, control logic, alarms, and historian trends into practical AI use cases and agent workflows
• Work with time-series operational data from DCS/SCADA and plant historians (preferably Emerson Ovation) to identify abnormal patterns, degradation, and performance losses
• Collaborate with sales and marketing, and reliability teams to validate AI insights against real plant conditions
• Support development and tuning of AI/analytics models using Python and data tools (focus on application rather than algorithm research)
• Integrate AI outputs into dashboards, alerts, and engineering workflows without impacting plant safety or control integrity
• Test, validate, and monitor AI solutions in live or near-real plant environments, ensuring reliability and low false-alarm rates
• Continuously improve AI performance using operational feedback, historical fault data, and domain knowledge
• Troubleshoot deployed analytics/AI tools and coordinate improvements with software or data teams.

AI Agent Development Engineer

• collaborate with cross-functional teams within Sun Life's IT function to understand IT process improvements using AI and translate them into effective solutions that can work at scale.
• implement and maintain robust pipelines for AI ready data, ensuring the integrity, security, and accessibility of data used for AI applications.
• working with Sun Life's Engineering Innovation and Architecture team, continuously research and evaluate emerging Generative AI and Agentic AI tools and techniques to identify opportunities for improvement and innovation.
• provide technical leadership and mentorship to junior team members, contributing to the growth and adoption of the AI capabilities within the firm.
• participate in the development of AI governance policies and best practices to ensure compliance with regulatory requirements and industry standards along with cost effectiveness.

Gen AI Development Specialist

• Collaborate with cross-functional teams within Sun Life's IT function to understand IT process improvements using AI and translate them into effective solutions that can work at scale.
• Implement and maintain robust pipelines for AI ready data, ensuring the integrity, security, and accessibility of data used for AI applications.
• Working with Sun Life's Engineering Innovation and Architecture team, continuously research and evaluate emerging Generative AI and Agentic AI tools and techniques to identify opportunities for improvement and innovation.
• Provide technical leadership and mentorship to junior team members, contributing to the growth and adoption of the AI capabilities within the firm.
• Participate in the development of AI governance policies and best practices to ensure compliance with regulatory requirements and industry standards along with cost effectiveness.
• Partnering with SunLife Enterprise teams, drive the needs of Sun Life by creating a collaborative development approach.

Specialist – Gen AI Development

• Own the vision, strategy, and multi-quarter roadmap for agentic AI solutions
• Lead the AI Modeling Platform (AMP) as a product by defining capabilities and prioritizing features
• Translate business problems into measurable value cases and track benefits realization
• Establish standards for agent safety, governance, and controls appropriate for regulated banking use
• Lead and grow a team of data scientists / ML engineers / decision scientists
• Drive end-to-end Agile delivery from discovery through scaling and lifecycle management
• Drive enterprise partnership and scale by aligning cross-functional stakeholders and cross-region teams
• Stay ahead of agentic AI/LLMOps and regulatory/MRM trends

AVP, AI Modeling Platform

• Lead and scale fraud-focused technology and AI services engagements across enterprise clients
• Act as a client-facing lead and trusted advisor, building strong stakeholder relationships and driving strategic fraud initiatives
• Bring hands-on expertise across modern fraud frameworks, fraud operations, risk controls, AI/ML-based fraud detection models, and fraud technology platforms
• Design and implement scalable fraud prevention, detection, and monitoring solutions across digital and enterprise environments
• Provide thought leadership on emerging fraud trends, AI-enabled fraud risks, behavioral analytics, identity intelligence, and real-time detection strategies
• Collaborate with cross-functional teams including engineering, cybersecurity, data science, product, and business stakeholders to deliver measurable outcomes
• Build, mentor, and scale a high-performing fraud technology team, fostering innovation and technical excellence
• Drive successful delivery execution, stakeholder alignment, and achievement of client and business objectives
• Support capability development, solution design, and practice growth initiatives within the fraud and risk management domain

Fraud AI Services Delivery Lead

• Benchmark design & execution: Build and maintain repeatable end-to-end benchmarks for database and AI workloads
• Database performance engineering: Evaluate throughput, latency, concurrency, scalability, and stability across OLTP/OLAP and mixed workloads.
• AI performance benchmarking: Measure and optimize performance for GPU/CPU inference pipelines, model serving, and data/feature pipelines; assess cost/performance tradeoffs.
• Tooling & automation: Develop harnesses, scripts, dashboards, and reproducible environments to run benchmarks consistently.
• Analysis & reporting: Produce clear reports, identify bottlenecks, and recommend fixes.
• Cross-functional collaboration: Partner with database engineers, AI engineers, the field teams and product management to define performance goals and acceptance criteria.
• Performance best practices: Establish standards for test hygiene, statistical rigor, hardware normalization, and benchmark governance.

Principal Performance Engineer, Database & AI Benchmarking

• Depending on the task, you may be asked to generate original content or assess AI-generated outputs.
• Deliver culturally relevant and appropriate content by applying local insight into tone, symbolism, visual cues, and market fit.
• Spot common issues such as visual artefacts, inconsistent style, translation errors, or cultural mismatches.
• Provide concise, structured annotations that can be used directly for model improvement.
• Apply evaluation guidelines consistently and participate in calibration and QA processes to ensure aligned scoring and judgment standards

AI Expert

• Supporting the delivery of managed services by assisting in the transition and operation of client processes
• Engaging in the design and development of automation frameworks to enhance service efficiency
• Participating in the continuous improvement of managed services processes, tools, and services
• Collaborating with delivery teams to optimize operational performance and manage delivery risks
• Utilizing project management skills to plan and execute deliverables within budgetary constraints
• Applying business process automation techniques to streamline client operations and reduce costs
• Conducting process performance analysis to identify opportunities for improvement and transformation
• Assisting in the development and implementation of workflow automation solutions
• Gathering and analyzing data to inform insights and recommendations for service enhancements
• Building and maintaining relationships with stakeholders to support service level management and delivery excellence

Hyper Automation Engineer – Associate, UiPath

• Managing and optimizing client service delivery processes within managed services
• Designing automation frameworks and developing solutions to enhance operational efficiency
• Implementing business process automation strategies to streamline workflows and reduce costs
• Leading project management efforts to validate timely delivery and performance excellence
• Utilizing analytical thinking to interpret data and inform insights and recommendations
• Collaborating with delivery teams to drive continuous process improvement and innovation
• Engaging stakeholders to understand needs and align service management strategies
• Navigating complex situations to build meaningful client relationships and inspire team growth

Senior Automation Engineer – UiPath, AI Managed Services

• Leading the transformation and optimization of managed services processes and tools to enhance operational efficiency
• Managing delivery teams and overseeing program performance to meet client expectations and service level agreements
• Implementing automation solutions and frameworks to streamline business processes and reduce operational costs
• Driving continuous improvement initiatives to enhance service delivery and client satisfaction
• Applying systems thinking to identify and address underlying problems and opportunities within managed services
• Coaching and motivating teams to solve complex problems and deliver quality results
• Engaging with stakeholders to validate outcomes, share perspectives, and incorporate feedback into service enhancements
• Developing and maintaining relationships with clients to support business transformation and strategic initiatives
• Overseeing budgetary management and resource allocation to optimize project delivery and performance
• Crafting and conveying clear, impactful messages that communicate the value and impact of managed services solutions

AIOps Transformation Lead – Senior Manager, AI Managed Services

• Design and build production-ready AI/ML systems with high reliability and scalability
• Work extensively with LLMs, RAG pipelines, and agentic frameworks
• Fine-tune and optimize models for real-world performance and efficiency
• Develop and deploy edge AI and computer vision solutions
• Architect and implement distributed, high-availability AI systems
• Optimize workloads across GPU architectures and compute environments
• Build on-demand LLM systems and intelligent automation pipelines
• Develop and research robotics teleoperation systems in simulation (MuJoCo, Isaac)
• Build scene and task generation toolchains in robotics simulators
• Develop reactive 3DGS-based end-to-end autonomous driving (E2E-AD) closed-loop simulators
• Deploy and train E2E-AD algorithms (UniAD, VAD, VADv2, etc.)

Senior AI/ML Expert

• Design, develop and maintain scalable ETL (Extract, Transform, Load) processes to efficiently extract data from various structured and unstructured sources, ensuring accuracy, consistency and performance optimization.
• Architect and manage database systems to support large-scale data storage and retrieval, ensuring high availability, security and efficiency in handling complex datasets.
• Integrate and transform data from multiple sources including APIs, on-premises databases and cloud storage, creating unified datasets to support data-driven decision-making across the organization.
• Collaborate with business intelligence analysts, data scientists and other stakeholders to understand specific data needs, ensuring the delivery of high-quality, business-relevant datasets.
• Monitor, troubleshoot and optimize data pipelines and workflows to resolve performance bottlenecks, improve processing efficiency and ensure data integrity.
• Develop automation frameworks for data ingestion, transformation and reporting to streamline data operations and reduce manual effort.
• Work with cloud-based data platforms and technologies such as AWS (Redshift, Glue, S3), Google Cloud (Big Query, Dataflow), or Azure (Synapse, Data Factory) to build scalable data solutions.
• Optimize data storage, indexing, and query performance to support real-time analytics and reporting, ensuring cost-effective and high-performing data solutions.
• Lead or contribute to special projects involving data architecture improvements, migration to modern data platforms, or advanced analytics initiatives.

Senior Consultant – Tech Consulting, AI and Data

• Supervise and lead a team of AI engineers, ensuring successful project execution and delivery
• Work closely with stakeholders to define AI strategy and align projects with business objectives
• Manage the AI development lifecycle, including planning, resource allocation, and monitoring progress
• Foster collaboration between AI teams and other departments to support seamless integration of AI solutions
• Provide regular updates to the Sr. Artificial Intelligence Manager on project status, challenges, and achievements
• Drive the integration of AI solutions into existing systems and processes
• Build out best practices and coding standards within the AI engineering team

AI Manager

• Review images and videos using predefined evaluation guidelines and scoring frameworks
• Assess realism, composition, lighting, motion, camera movement, and production quality
• Provide clear written justifications for evaluation decisions
• Maintain high consistency and accuracy across large annotation workloads
• Identify quality issues and inconsistencies in generated or real-world media
• Apply structured reasoning when following complex annotation instructions
• Incorporate feedback and guideline updates into ongoing annotation work
• Collaborate with remote teams working on AI training data and evaluation

Video Quality Evaluator – AI Training Data

• Develop AI products and systems
• Collaborate with cross-functional teams
• Involve in AI projects and enhancements

AI Subject Matter Expert

• Serve as the technical authority and hands-on leader in designing, building, and scaling next-generation Agentic AI solutions for autonomous network operations.
• Be instrumental in the technical implementation of the core "AI brain" framework, working across the five-layer architecture of autonomous agents designed for continuous coverage: detection, aggregation, synthesis, investigation, and recommendation.
• Drive the core technical efforts in Agentic Workflow Orchestration, including designing robust agent-to-agent communication patterns and structuring the overall task flow.
• Lead the engineering and optimization of Large Language Model (LLM) components through advanced Prompt Engineering, Fine-tuning, and Context Engineering (RAG pipelines).
• Design and deliver high-precision Retrieval Augmented Generation (RAG) systems using vector databases and semantic search to ground models in enterprise data.

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