Experience:

• 3 to 5 years of software engineering experience
• Strong, demonstrable Python fundamentals

Qualification:

• Graduate - B.Tech/B.E. - Computers, Electronics/Telecommunication
• PG - M.Sc. – Computers
• M.Tech - Any Specialization
• MCA - Computers

Responsibilities:

• Build and integrate Agentic AI workflows including tool use, memory, planning loops, MCP integrations
• Implement RAG pipelines end-to-end including document ingestion, chunking, embedding, vector retrieval, evaluation
• Integrate LLMs via API with prompt engineering, function calling, structured outputs, context management
• Use AI coding agents as part of development and validate AI-generated output
• Write clean, maintainable, production-quality Python code following SOLID principles and design patterns
• Apply test-driven development and maintain unit and integration tests
• Participate in code reviews, Agile/Scrum ceremonies, and JIRA-driven workflows
• Work within Git-based version control following branching, PR, and code review processes
• Build data pipelines for ingestion, transformation, and analysis using Python, numpy, pandas
• Perform exploratory data analysis and generate visual summaries using Matplotlib, Seaborn, Plotly
• Contribute to data quality assessment and transformation workflows

Additional responsibilities:

• Explain technical decisions clearly to non-technical stakeholders
• Adapt quickly to new domains and technology stacks
• Contribute directly to client engagements alongside a senior-leaning team

Nice to have:

• Experience with AI coding tools (Claude Code, OpenAI Codex, GitHub Copilot)
• Vector database experience (Pinecone, Weaviate, ChromaDB, Qdrant)
• NLP fundamentals (tokenization, text classification, similarity, named entity recognition)
• Applied statistics and advanced exploratory data analysis
• Conversational AI or chatbot development experience
• Cloud platform exposure (AWS, Azure, GCP)

More skills:

Agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI), LLM integration (OpenAI, Anthropic Claude, Google Gemini), RAG concepts (chunking, embeddings, vector stores, retrieval evaluation), SOLID principles, Design patterns, Test-driven development, Unit testing, numpy, pandas, Visualization libraries (Matplotlib, Seaborn, Plotly), ML concepts, VS Code or comparable IDE, Git version control, Agile/Scrum

Other:

• Work on real enterprise AI problems across diverse client industries
• Exposure to agentic AI, RAG, NLP, and data engineering within a single role
• Ownership of contributions with real client deployments
• Team values clean engineering and intellectual curiosity
• Competitive compensation aligned with market standards