- 8–12+ years of overall software engineering experience
- 3+ years of strong hands-on experience in AI/ML, GenAI or related AI engineering
- Strong hands-on Python development
- Strong recent hands-on experience building GenAI/LLM-based applications
- Strong experience with LLMs, prompt engineering, structured outputs and tool/function calling
- Hands-on experience with RAG, embeddings, vector databases, document processing, chunking, retrieval and reranking
- Hands-on experience with AI agents and agent orchestration, including multi-step workflows, tool-using agents, memory/state management and human-in-the-loop patterns
- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar frameworks
- Good understanding of MCP and emerging standards for connecting AI agents with enterprise systems and tools
- Experience with backend development using FastAPI, Flask, Django or similar frameworks
- Strong understanding of REST APIs, microservices and distributed application architecture
- Experience integrating enterprise applications, databases and third-party APIs
- Strong coding, debugging, troubleshooting and performance optimisation skills
- Experience owning solution architecture and technical design for enterprise applications
- Experience taking solutions from discovery/prototype through development and production deployment
- Hands-on exposure to at least one major cloud platform: Azure, AWS or GCP
- Experience with Docker, Kubernetes, CI/CD, cloud-native application deployment, API management, logging/monitoring and identity/access management
- SQL and relational databases; NoSQL databases; vector databases
- Data ingestion and transformation pipelines; API-based integration; event-driven/asynchronous processing
- Understanding of enterprise authentication/authorization, data privacy, PII handling and enterprise security requirements
- Understanding of secure AI architecture, data protection, prompt/input security, AI guardrails, logging, auditability, monitoring, evaluation, regression testing, scalability and cost management
- Experience leading technical teams while continuing to contribute to development
- Strong client-facing and communication skills




- Experience working in Agile delivery environments
- Ability to move from Client Problem → Solution Architecture → Technical Design → Team Guidance → Hands-on Coding → Code Review → Deployment → Production Support

Good-to-Have Skills

- Experience with Azure AI Foundry, AWS Bedrock, Google Vertex AI or similar enterprise AI platforms
- Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini or equivalent models
- Traditional ML/ML engineering knowledge
- LLM evaluation frameworks
- AI guardrails and responsible AI
- LLM observability and tracing
- Model and prompt evaluation
- Token, latency and cost optimisation
- Experience building enterprise AI accelerators or reusable AI platforms
- Experience with multi-agent or agentic AI solutions
- Experience modernising existing enterprise applications using AI
- Microsoft Fabric or enterprise data platforms
- BFSI, financial services or other regulated enterprise environments
- AI security and responsible AI practices
- Experience supporting technical proposals, estimations and solution presentations
- Experience mentoring engineers and building engineering standards or reusable frameworks
- Git-based development, branching, pull requests and code reviews
- Experience with API management, secrets/configuration management and production troubleshooting

Key Responsibilities

- Understand business requirements and translate them into the right technical solution
- Own overall architecture and technical design of AI, GenAI and agentic AI solutions
- Define application architecture, AI/LLM components, APIs, integrations, data flows, security and deployment approach
- Evaluate technology and model options based on business need, cost, performance, security and scalability
- Create architecture diagrams, technical design documents,



API specifications and implementation guidelines
- Identify technical risks and drive practical solutions
- Actively contribute to coding throughout the project
- Build critical modules, prototypes, reusable components and integrations
- Develop and integrate LLM applications, RAG pipelines, AI agents and APIs
- Support complex coding, integration and performance issues
- Conduct code reviews and ensure good engineering practices
- Improve code quality, performance, security and maintainability
- Lead and guide AI/ML engineers, backend developers and other technical team members
- Break solutions into technical work packages and guide implementation
- Support estimation, sprint planning and technical task allocation
- Track technical progress and address dependencies/blockers
- Mentor team members and improve technical capabilities
- Review designs and code before higher environments
- Ensure technical quality throughout the project
- Work closely with Project Managers, Business Analysts, Solution Architects, QA and DevOps teams
- Own technical delivery and ensure alignment with agreed architecture
- Participate in client discovery and technical workshops
- Understand client landscape, integrations, data, security and infrastructure constraints
- Explain architecture and technical decisions to technical and business stakeholders
- Present solution architecture and technical options during client reviews
- Support pre-sales with technical solutioning, estimates, architecture and feasibility assessments
- Handle technical questions and challenges during client discussions
- Take AI solutions beyond prototype into production, including security, governance, evaluation, monitoring, scalability, performance and cost management something around - Anthropic Claude certifications (particularly CCAF for architects), Microsoft AI-103, AWS Certified Generative AI Developer – Professional.

Education / Qualification

- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology or a related discipline
- Equivalent solid hands-on engineering experience may also be considered

📌 Tech Lead (Maharashtra)
🏢 Latent Bridge
📍 Maharashtra