Senior AI Engineer - Agentic & Generative AI
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Senior AI Engineer - Agentic & Generative AI
Location
Pune, Maharashtra, India (Hybrid)
Experience
Senior
Posted
Jul 18, 2026
Apply by
August 17, 2026
Applicants
0
Early applicantEasy applyFull-timeHybrid
Job Description
Role: Senior AI Engineer - Agentic & Generative AI
Experience: 10+ 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 seasoned Software Engineer with hands-on Agentic and Generative AI experience to provide technical leadership on client engagements. This is a hands-on role - you will design solutions, write code, and deliver alongside the team while also setting technical direction, mentoring engineers, and engaging directly with client stakeholders.
You will work heavily with AI coding agents to design and deliver solutions, which means strong prompt engineering discipline and the ability to direct AI-assisted development workflows are core to how this role operates. In a consulting environment, adaptability and the ability to bring structure to ambiguous problems are as important as technical depth.
Key Responsibilities:
Agentic AI Solution Design & Delivery
- Architect and deliver Agentic AI systems - multi-agent orchestration, tool use, memory, planning loops, and MCP integrations
- Design RAG pipelines and agentic workflows tailored to client knowledge and data landscapes
- Lead LLM integration strategy - model selection, prompt engineering, context management, and structured outputs across providers
- Use AI coding agents (Claude Code, Codex, Copilot, or equivalent) as a primary development tool; direct and validate AI-generated output with precision
Technical Leadership & Client Engagement
- Provide technical leadership on engagements - own solution design, drive requirements gathering and analysis, and guide the team through delivery
- Lead client discovery sessions, technical scoping, and solution presentations; translate ambiguous business problems into well-defined AI solutions
- Conduct design reviews, enforce engineering standards, and mentor junior and mid-level engineers
- Drive technology selection; establish reusable patterns and internal frameworks that improve delivery across the team
Data, Analytics & Engineering
- Apply statistical analysis and EDA to client data problems; generate charts, graphs, and visual summaries that communicate findings clearly to both technical and non-technical audiences
- Contribute to data quality assessment, pipeline design, and insight delivery using Python, numpy, and pandas
- Write clean, testable code following SOLID principles and design patterns; apply test-driven development practices and write unit tests as a standard part of delivery
Practice Development
- Stay current on the Agentic AI landscape and bring relevant advances into SPAR's delivery practice
- Contribute to internal knowledge assets, accelerators, and capability building
Required:
- 10+ years in software engineering with at least 1 year focused on Generative and Agentic AI
- Hands-on experience with at least one agentic framework - LangChain, LangGraph, AutoGen, CrewAI, or equivalent
- Direct experience prompting and integrating major LLMs - OpenAI, Anthropic Claude, Google Gemini, or similar
- Hands-on use of AI coding agents - Claude Code, OpenAI Codex, GitHub Copilot, or equivalent
- Experience with MCP integrations, agentic workflows, and multi-agent system design
- Strong prompt engineering skills - systematic, structured, and testable prompting practices
- Foundational understanding of ML concepts - how models are trained, data preparation, purpose and mechanics of fine-tuning, and when to apply pre-trained vs. fine-tuned models
- System design proficiency - distributed systems thinking, API design, scalability and reliability patterns
- Applied statistics and EDA - comfortable with data exploration, distributions, correlation, and translating findings into actionable insights
- Proficiency with Python, numpy, and pandas; experience with visualization libraries (matplotlib, seaborn, Plotly, or equivalent)
- Test-driven development practices and unit testing experience
- Experience leading technical workstreams or teams on client-facing consulting engagements
- Exceptional communication - equally effective whether writing a precise technical spec or presenting to a non-technical audience
- Agile methodology experience; comfortable owning delivery timelines and managing technical risk
- High adaptability - thrives across client domains and technology stacks; fast, self-directed learner
Desired:
- Conversational AI and chatbot design experience
- Hands-on experience with data analytics and data science tooling beyond EDA
- Deeper ML experience - has built, trained, and evaluated models beyond conceptual understanding
- Transformer architecture depth - model behavior, failure modes, tokenization, and fine-tuning tradeoffs
- MLOps and model lifecycle management - experiment tracking, deployment pipelines, monitoring
- Multi-modal AI, knowledge graph construction, or domain-specific model adaptation
Why SPAR Solutions
- Direct exposure to high-impact enterprise problems across industries
- Hands-on technical role with real leadership influence - you design, build, and set direction
- A fast-moving team where intellectual rigor and ownership are valued over hierarchy
- Opportunity to shape SPAR's AI practice - the frameworks and standards you establish become the team's foundation
- Compensation competitive with the current market
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
Key Responsibilities
- Architect and deliver Agentic AI systems including multi-agent orchestration and MCP integrations
- Design RAG pipelines and agentic workflows tailored to client knowledge landscapes
- Lead LLM integration strategy including model selection and prompt engineering
- Use AI coding agents as primary development tools and validate generated output
- Provide technical leadership on client engagements and drive requirements gathering
- Lead client discovery sessions and translate business problems into AI solutions
- Conduct design reviews and mentor junior and mid-level engineers
- Apply statistical analysis and EDA to client data problems
- Write clean, testable code following SOLID principles and TDD practices
Requirements
- B.Tech/B.E. in Computers
- Electronics/Telecommunication
- M.Sc. in Computers
- M.Tech in Any Specialization
- MCA in Computers
Skills Required
PythonnumpypandasLangChainLangGraphAutoGenCrewAIOpenAI APIAnthropic ClaudeGoogle GeminiClaude CodeOpenAI CodexGitHub CopilotMCP integrationsPrompt engineeringLLM integrationRAG pipelinesMulti-agent system designStatistical analysisEDAmatplotlibseabornPlotlyTest-driven developmentUnit testingAgile methodologyTechnical leadershipCommunicationAdaptabilityMentoringProblem solvingClient engagementConversational AIChatbot designData analyticsData science toolingModel training and evaluationTransformer architectureMLOpsModel lifecycle managementMulti-modal AIKnowledge graph construction
Benefits
- Competitive compensation
- Direct exposure to high-impact enterprise problems
- Hands-on technical role with leadership influence
- Opportunity to shape AI practice
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