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AI Engineer – FDE, Forward Deployed Engineer

LLM Engineer

• Utilize SAP BTP AI Core and AI Launchpad services to deploy and manage AI solutions
• Collaborate with cross-functional teams to integrate AI/ML solutions into SAP BTP environments
• Design and implement AI/ML models, with a focus on generative AI techniques and large language models
• Develop and maintain scalable and robust applications using Python and Go programming languages
• Engage in prompt engineering to fine-tune LLMs for specific use cases and ensure optimal performance
• Stay abreast of the latest advancements in AI/ML and SAP BTP to continuously improve our offerings
• Provide technical expertise and support for SAP BTP AI Business services to enhance business processes
• Document and present AI/ML project results to stakeholders and provide actionable insights
• Responsible for decision-making, optimizing processes, resource management, and overseeing team management as needed for task execution
• Accountable for allocating personnel, supervising team members, assigning tasks, ensuring that the team has the necessary tools and support to succeed in their roles and optimizing and evaluating their performance to meet organizational goals.

Senior SAP BTP LLM Developer

• Design, build, and deploy end-to-end software workflows and automation across the entire GTM stack.
• Integrate LLM APIs, autonomous AI agents, and custom middleware into existing sales, marketing, and customer retention systems.
• Optimize data pipelines ensuring seamless flow between lead generation, intent signals, pipeline movement, and customer lifecycle data.
• Evaluate, benchmark, and implement emerging AI tools and frameworks to accelerate lead scoring, personalization, automated prospecting, and churn prediction.

GTM, AI Engineer

• Design, develop, and deploy production-ready AI infrastructure and machine learning models
• Architect Agentic AI workflows and RAG systems for enterprise use cases
• Build high-performance, scalable data pipelines to support AI/ML model training and inference
• Develop and implement solutions leveraging Generative AI, Computer Vision, and NLP
• Optimize model performance, latency, and cost for production environments
• Stay current with emerging AI/ML frameworks, tools, and best practices
• Design and develop front-end and back-end components to support production applications
• Build robust APIs and integrate AI/ML models into web and enterprise applications
• Ensure application scalability, security, and performance across the stack
• Provide ongoing production support for Production applications, including troubleshooting, root cause analysis, and issue resolution
• Monitor application health, performance, and reliability post-deployment
• Create and maintain support documentation, runbooks, and knowledge base articles
• Respond to incidents and manage escalations in a timely manner

AI Full Stack Engineer

• Design, develop, and maintain the LLM-powered backend services using Python and FastAPI.
• Implement retrieval-augmented generation (RAG) to fetch structured and unstructured data from OXRED.
• Use frameworks like LangChain, LlamaIndex, or Haystack to manage context retrieval, query routing, and summarization.
• Integrate the chatbot logic with the existing OXRED AskOX frontend.
• Design, implement, and validate support for diverse fleet analytics use cases including fleet summaries, vehicle diagnostics, predictive insights, and performance metrics.
• Ensure secure and efficient data flow between OXRED APIs and the AskOX backend.
• Evaluate and improve retrieval accuracy, latency, and hallucination rates.
• Maintain technical documentation and API specifications.

Machine Learning Engineer – LLM, GenAI

• Develop AI-powered workflows for: BOQ Generation, Quantity Takeoff, Formwork Estimation, Shop Drawing Automation, IFC Processing, Floor Plan Analysis and Generation, Drawing Intelligence, CAD Automation, Revit Automation, AI Model Integration, Geometry Processing, Document Intelligence
• Improve: Accuracy, Performance, Automation, Engineering logic, Scalability
• Collaborate with architects and engineers to solve real-world construction problems.

Senior AEC/BIM AI Engineer

• Design, build, and deploy AI-powered applications using Large Language Models, multimodal models, and intelligent agents.
• Develop scalable AI solutions that automate enterprise workflows and enhance customer experiences.
• Build reusable AI services, APIs, and components that integrate seamlessly into Aion's platform.
• Rapidly prototype, validate, and productionize AI use cases across multiple industries.
• Develop advanced prompt engineering strategies, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows.
• Build multi-agent systems capable of reasoning, planning, and executing complex enterprise tasks.
• Integrate foundation models from leading providers while optimizing performance, reliability, and cost.
• Evaluate, fine-tune, and optimize AI models for production use cases.
• Integrate AI applications with enterprise systems, databases, APIs, and third-party platforms.
• Build scalable inference pipelines and AI workflows that support production deployments.
• Collaborate with platform and infrastructure teams to optimize model serving, orchestration, and deployment.
• Implement robust evaluation frameworks to continuously measure AI quality and performance.
• Optimize AI applications for latency, accuracy, scalability, and operational efficiency.
• Implement observability, monitoring, logging, and evaluation pipelines for AI systems.
• Ensure AI solutions meet enterprise requirements for security, privacy, governance, and compliance.
• Troubleshoot production AI systems and continuously improve model performance through experimentation and feedback.
• Write clean, maintainable, and production-quality code following engineering best practices.
• Conduct code reviews and contribute to technical design discussions.
• Collaborate closely with Product, Platform, Infrastructure, and Customer Success teams to deliver customer-centric AI solutions.
• Stay current with emerging AI research, tools, and technologies, and evaluate their applicability to Aion's platform.

• Design, develop, and maintain the software solution (Studio) with drag-drop flow builder and execution engine that integrates multiple channels like voice, SMS, and chatbot with the Five9 contact center voice solution
• Modernize and re-architect the existing Studio product to use Java microservices on GCP
• Software design and development, testing and documentation across backend, front-end, and interaction management platforms to deliver end-to-end features
• Work with product owners and designers to expand the feature set and create high-quality user interfaces
• Take operational responsibility for the performance and quality of services owned by your team
• Participate in an on-call rotation and deep dive into cutting edge technologies
• Collaborate with the products team to transfer ideas into products

Senior Software Engineer – AI

• Design and engineer software with customer/user experience as primary objective
• Define, create, and provide oversight of engineering and design solutions
• Collaborate with various feature teams to produce high-quality software
• Work within a platform or feature team to engineer complex software

Principal Engineer, AI

• Develop and implement end-to-end AI-driven applications, integrating generative AI models
• Build and maintain scalable front-end interfaces using modern web frameworks (React, Angular, Vue.js)
• Design and develop robust back-end services using Node.js, Python, or other back-end technologies
• Integrate large language models (LLMs) and multimodal AI models into applications
• Optimize application performance, ensuring efficiency in AI inference and API response times
• Develop and maintain RESTful and GraphQL APIs for AI model interaction
• Deploy AI applications on cloud platforms (AWS, GCP, Azure) using containerization and serverless technologies
• Ensure security, scalability, and compliance of AI-driven applications
• Stay up to date with the latest advancements in Generative/Agentic4 AI, web development, and cloud technologies

Full Stack AI Engineer

• Building secure, AI search and retrieval for large‑scale enterprise document platforms using Azure AI Search and Azure OpenAI.
• Experience with large‑scale enterprise document repositories.
• Strong understanding of Retrieval‑Augmented Generation (RAG), Vector search, and experience grounding LLM responses in enterprise data sources.
• Index design for unstructured enterprise documents using hybrid search (keyword + vector).
• Designing prompts that constrain responses to source documents, reduce hallucinations, and support citation‑based answers.
• Strong backend engineering experience (Java, Python).
• Experience building APIs or services that orchestrate Search, Retrieval, LLM calls.
• Implement security-aware retrieval, including Document‑level access control.
• Experience measuring and improving retrieval relevance, answer accuracy, and latency across search and generation.
• Integrating AI search into internal applications.

AI/ML Engineer

• Lead the design, development, and ownership of AI-powered internal platforms and systems, including initiatives built from the ground up.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Design and implement AI-driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
• Embed AI capabilities into customer-facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
• Build full-stack systems spanning backend services, APIs, data layers, and frontend interfaces.
• Translate ambiguous business and operational problems into scalable, maintainable, AI-enabled technical solutions.
• Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
• Collaborate closely with engineers, teams, and stakeholders across the company to identify high-impact opportunities and drive adoption.

AI Engineer II

• Develop and implement Machine Learning and Generative AI solutions to solve business challenges.
• Build, test, and optimize AI models using Python and modern AI/ML frameworks.
• Design and develop Retrieval-Augmented Generation (RAG) applications using enterprise knowledge sources.
• Assist in developing AI Agents and multi-agent workflows using frameworks such as LangChain, LangGraph, CrewAI, or similar technologies.
• Perform data preparation, feature engineering, model training, evaluation, and performance monitoring.
• Support deployment and operationalization of AI models using MLOps best practices.
• Integrate AI solutions with enterprise applications, APIs, databases, and cloud platforms.
• Collaborate with business stakeholders, developers, and data teams to gather requirements and deliver AI-driven solutions.
• Conduct research on emerging AI technologies, tools, and frameworks and recommend innovative solutions.
• Create technical documentation, test cases, and deployment artifacts for developed solutions.
• Participate in code reviews, knowledge-sharing sessions, and continuous improvement initiatives.

Associate AI-ML Engineer

• Build & support automation requirement & opportunities across analytics programs
• Build Power BI dashboards, semantic models, KPI scorecards, executive reports
• Partner with BU stakeholders to identify AI use cases and deliver intelligent knowledge discovery capabilities.
• Design and develop monitoring and QA automation solutions to streamline processes, reduce manual effort, and improve operational efficiency.
• Work with stakeholders in providing additional analysis based on specific needs
• Support and contribute to various GenAI initiatives across the organization.
• Research and stay UpToDate with the latest advancements in generative AI technologies, models, and frameworks.

Senior Analyst – AI Engineer

Computer Vision Engineer

• Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)
• Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
• Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX
• Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.
• Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.
• Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.

Machine Learning Engineer – IV, Computer Vision

• Design, build, and deploy scalable Artificial Intelligence and Machine Learning solutions for real-world business problems.
• Develop, train, evaluate, and optimize machine learning models using structured and unstructured data.
• Build robust data pipelines for feature engineering, model training, validation, and inference.
• Deploy ML models into production environments and monitor performance, scalability, and reliability.
• Collaborate with engineering teams to integrate AI capabilities into enterprise applications and APIs.
• Evaluate new AI techniques, frameworks, and technologies to improve solution effectiveness.
• Implement model monitoring, retraining strategies, and MLOps best practices for production systems.
• Work closely with product managers and business stakeholders to translate business requirements into AI-driven solutions.
• Mentor junior engineers by conducting code reviews and sharing best practices in AI and software engineering.
• Ensure compliance with security, governance, and responsible AI principles throughout the development lifecycle.

Senior AI/ML Engineer

• Translate ambiguous stakeholder requirements into structured solutions, user flows, and deliverables
• Design system architecture, making decisions around scalability, maintainability, and security
• Build and deliver end-to-end features across frontend and backend with full ownership
• Rapidly prototype AI-enabled solutions and evolve them into production-ready systems
• Improve and scale an existing Python-based application, addressing backlog, performance, and UX gaps
• Define and implement UX flows and usability improvements (not visual design, but user journeys)
• Integrate with APIs, including AI-driven services, and design robust data flows
• Apply secure development practices and ensure systems are reliable and maintainable
• Balance speed of delivery with long-term engineering quality and structure
• Contribute to and elevate engineering practices (architecture, SDLC, testing) through hands-on work
• Collaborate with stakeholders and team members while operating with a high degree of independence

Senior Full Stack AI Engineer, Contract

• Architect and deliver Agentic AI systems - multi-agent orchestration, tool use, memory, planning loops, and MCP integrations
• Design RAG pipelines and agentic workflows tailored to client knowledge and data landscapes
• Lead LLM integration strategy - model selection, prompt engineering, context management, and structured outputs across providers
• Use AI coding agents (Claude Code, Codex, Copilot, or equivalent) as a primary development tool; direct and validate AI-generated output with precision
• Provide technical leadership on engagements - own solution design, drive requirements gathering and analysis, and guide the team through delivery
• Lead client discovery sessions, technical scoping, and solution presentations; translate ambiguous business problems into well-defined AI solutions
• Conduct design reviews, enforce engineering standards, and mentor junior and mid-level engineers
• Drive technology selection; establish reusable patterns and internal frameworks that improve delivery across the team
• Apply statistical analysis and EDA to client data problems; generate charts, graphs, and visual summaries that communicate findings clearly to both technical and non-technical audiences
• Contribute to data quality assessment, pipeline design, and insight delivery using Python, numpy, and pandas
• Write clean, testable code following SOLID principles and design patterns; apply test-driven development practices and write unit tests as a standard part of delivery
• Stay current on the Agentic AI landscape and bring relevant advances into SPAR's delivery practice
• Contribute to internal knowledge assets, accelerators, and capability building

Senior AI Engineer – Agentic, Generative AI

• Build and integrate Agentic AI workflows: tool use, memory, planning loops, and MCP integrations using frameworks such as LangChain, LangGraph, AutoGen, or CrewAI
• Implement RAG pipelines end-to-end: document ingestion, chunking, embedding, vector retrieval, and evaluation
• Integrate LLMs via API: prompt engineering, function calling, structured outputs, and context management across providers such as OpenAI, Anthropic, and Gemini
• Use AI coding agents (Claude Code, Codex, Copilot, or equivalent) as part of day-to-day development; direct and validate AI-generated output effectively
• Write clean, maintainable, production-quality Python code following SOLID principles and established design patterns
• Apply test-driven development practices; write and maintain unit and integration tests as a standard part of delivery
• Participate in code reviews, Agile/Scrum ceremonies, and JIRA-driven delivery workflows
• Work within Git-based version control; follow established branching, PR, and code review processes
• Build data pipelines for ingestion, transformation, and analysis using Python, numpy, and pandas
• Perform exploratory data analysis; generate charts, graphs, and visual summaries using Matplotlib, Seaborn, Plotly, or equivalent
• Contribute to data quality assessment and transformation workflows as part of broader AI solution delivery

AI Engineer – Agentic, Generative AI

• Own and define enterprise‑scale AIOps, GenAI, and Agentic AI platform strategy across multiple clients/accounts
• Act as final technical authority for architecture, design reviews, risk mitigation, and production readiness
• Lead operations and governance , including CAB ownership, platform stability, SLAs, KPIs, and continuous improvement
• Drive industrialized adoption of GenAI & Agentic AI , converting PoCs into secure, scalable, production solutions delivering measurable business outcomes
• Lead, mentor, and manage multi‑location AI/Automation teams , while advising senior stakeholders and supporting presales and roadmap decisions

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