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, 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

• 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

• Collaborate with product managers, data scientists, and software engineers to identify AI/ML opportunities and develop innovative solutions.
• Implement and deploy AI/ML algorithms and models into production environments.
• Optimize and fine-tune AI/ML models to improve accuracy and efficiency.
• Conduct experiments, perform data analysis, and present findings to stakeholders.
• Develop and maintain documentation for AI/ML algorithms, models, and solutions.
• Stay up-to-date with the latest AI/ML research and technologies and apply them to improve our platform.
• Mentor and provide technical guidance to junior AI/ML engineers or team members.

AI Lead Engineer, Prompt Engineering, RAG, LLMs

• Designing and developing data solutions to transform raw data into actionable insights
• Leveraging advanced analytics and statistical techniques to extract insights from large datasets
• Conducting exploratory and descriptive analysis to solve complex business problems
• Creating data visualizations to inform strategic decisions and drive business growth
• Utilizing machine learning and artificial intelligence to enhance data-driven decision making
• Building and managing data pipelines and data lakes for efficient data processing
• Implementing data science algorithms and workflows to optimize data analysis
• Collaborating with clients to understand their data needs and deliver tailored solutions
• Confirming data quality and integrity throughout the data engineering process
• Mentoring junior team members and guiding them in data science methodologies

LLM Engineer jobs in India

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