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
LinkedIn: https://www.linkedin.com/company/spar-solutions-llc
Twitter: https://twitter.com/sparsolutions
Facebook: https://www.facebook.com/SPARsolutions
