Role: AI Engineer - Agentic & Generative AI Experience: 3 to 5 years Education: Graduate - B.Tech/B.E. - Computers, Electronics/Telecommunication; PG - M.Sc. – Computers, M.Tech - Any Specialization, MCA - Computers Location: Pune. About SPAR Solutions SPAR Solutions is a software and AI consulting and services firm delivering enterprise-grade solutions across diverse client industries. Our AI practice spans agentic automation, Generative AI product development, RAG-powered knowledge systems, and data-driven analytics — across the full lifecycle from research and prototyping through production deployment. About the Role We are looking for a mid-level Software Engineer with a strong engineering foundation and hands-on Generative and Agentic AI experience. Software engineering fundamentals: Clean code, testability, design patterns, and Delivery discipline are the baseline. Agentic and Generative AI is the focus layer you bring on top. You will contribute directly to client engagements: building agentic pipelines, integrating LLMs, and delivering well-engineered solutions alongside a senior-leaning team. In a consulting environment, the ability to ramp quickly on new domains and technologies is as valuable as your core skill set. Key Responsibilities: Agentic AI Development - 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 Software Engineering - 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 Data & Analytics - 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 Required - 3 to 5 years of software engineering experience with strong, demonstrable Python fundamentals - Hands-on experience with at least one agentic AI framework - LangChain, LangGraph, AutoGen, CrewAI, or equivalent - Experience prompting and integrating at least one major LLM - OpenAI, Anthropic Claude, Google Gemini, or similar - Working knowledge of RAG concepts - chunking strategies, embeddings, vector stores, and retrieval evaluation - Familiarity with MCP integrations and agentic workflow patterns - Strong prompt engineering skills - structured, systematic, and iterative approach - Well versed in use of SOLID principles, common design patterns, and clean code practices - Test-driven development and unit testing experience - Proficiency with numpy, pandas, and at least one visualization library (Matplotlib, Seaborn, or Plotly) - Foundational understanding of ML concepts - how models are trained, data preparation, and the purpose of fine-tuning - VS Code or comparable IDE; Git version control - Agile/Scrum experience - Strong written and verbal communication - able to explain technical decisions clearly to non-technical stakeholders - Adaptable and quick to learn - comfortable switching across technology stacks and client domains Desired: - AI coding tools - Claude Code, OpenAI Codex, GitHub Copilot, or similar - Vector database experience - Pinecone, Weaviate, ChromaDB, Qdrant, or equivalent - NLP fundamentals - tokenization, text classification, similarity, named entity recognition - Applied statistics and EDA experience beyond standard pandas workflows - Conversational AI or chatbot development experience - Cloud platform exposure - AWS, Azure, or GCP Why SPAR Solutions - Work on real enterprise AI problems across diverse client industries — not internal tooling or incremental maintenance - Grow fast — exposure to agentic AI, RAG, NLP, and data engineering within a single role alongside a senior team - Your contributions ship to real client deployments; ownership is real, not simulated - A team that values clean engineering and intellectual curiosity equally - Compensation competitive with current market standards for this level Contact Details: Talent Acquisition Team HR Department / SPAR Solutions Address: SPAR Solutions India Pvt. Ltd. Pune IT Park, B-503, Bhau Patil Marg, 34 Aundh Road, Bopodi, Pune, Maharashtra, India. Pin Code: 411020. Website: [sparsolutions.com](http://sparsolutions.com/) LinkedIn: https://www.linkedin.com/company/spar-solutions-llc Twitter: https://twitter.com/sparsolutions Facebook: https://www.facebook.com/SPARsolutions