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About the role
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
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