Join a dynamic team as an AI Engineer focusing on Agentic and Generative AI to build and integrate cutting-edge AI solutions in a consulting environment.

About the Company

SPAR Solutions is a leading software and AI consulting firm dedicated to delivering enterprise-grade solutions across a variety of client industries. Our specialization in AI spans agentic automation, Generative AI product development, RAG-powered knowledge systems, and data-driven analytics. Our team engages in comprehensive project lifecycles - from initial research and prototyping to full-scale production deployment.

Role Overview

We are seeking a mid-level AI Engineer with a solid software engineering foundation coupled with hands-on experience in Generative and Agentic AI. Your expertise will enhance our consulting solutions by contributing to client engagements in building agentic AI workflows, integrating large language models (LLMs), and delivering meticulously engineered solutions in collaboration with a senior-oriented team.

Key Responsibilities

• Agentic AI Development: Construct and integrate workflows utilizing agentic AI frameworks (LangChain, LangGraph, AutoGen, or CrewAI). Implement RAG pipelines comprehensively, integrating document ingestion processes, chunking, embedding, and vector retrieval.
• Software Engineering: Develop clean, maintainable, production-quality Python code abiding by SOLID principles. Engage in test-driven development and maintain rigorous testing standards.
• Data & Analytics: Develop data pipelines for effective ingestion and analysis using tools like Python, numpy, and pandas. Conduct exploratory data analysis and generate visual summaries using libraries like Matplotlib and Plotly.

Tech Stack

• Programming Languages: Python
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI
• LLMs: OpenAI, Anthropic, Google Gemini
• Data Tools: NumPy, Pandas, Matplotlib, Seaborn, Plotly
• Version Control: Git
• Development Practices: Agile/Scrum methodologies

Salary

Compensation for this position is expected to be in the range of ₹80,000 - ₹1,20,000 per month, competitive with market standards and reflective of your experience and capabilities.

Requirements

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.
• Experience with VS Code or comparable IDE; Git version control.
• Agile/Scrum experience.
• Strong written and verbal communication skills, able to explain technical decisions clearly to non-technical stakeholders.
• Adaptable and quick to learn, comfortable switching across technology stacks and client domains.

Desired:

• Experience with 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.
• Exposure to cloud platforms - AWS, Azure, or GCP.

Benefits

• Opportunity to work on real enterprise AI problems across diverse client industries.
• Rapid growth opportunities with exposure to agentic AI, RAG, NLP, and data engineering.
• Real ownership of your contributions, impacting actual client deployments.
• A team that values both clean engineering and intellectual curiosity.
• Competitive compensation aligned with current market standards for this level.