Lead AI Engineer

Lead AI Engineer

Experience: 8+ Years

Location: Coimbatore / Hybrid

Joining: Immediate or within 30 days

About Techjays

At Techjays, we help businesses reimagine how they build, operate, and scale through AI. We focus on developing secure, scalable, production-grade AI solutions that solve real business problems and deliver measurable outcomes.

Our engineering team brings experience from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We combine strong engineering fundamentals with an execution-focused mindset to build advanced AI systems for global clients.

About the Role

We are looking for a Lead AI Engineer to drive the architecture and development of scalable backend systems and AI-powered applications.

In this role, you will lead the technical design and implementation of Python-based systems, oversee LLM integrations and RAG pipelines, and develop agentic AI workflows for production environments. You will take ownership of complex engineering challenges, establish coding and architectural standards, and mentor engineers to deliver reliable, maintainable, and high-performing solutions.

This is a hands-on technical leadership role for someone who can translate complex requirements into practical engineering solutions and take them from design to production.

Key Responsibilities

1. Backend Engineering & System Architecture

• Design and develop scalable, secure backend systems using Python and frameworks such as Django or Flask.
• Architect RESTful APIs, WebSocket services, and distributed systems that support high-performance applications.
• Apply design patterns, algorithms, and data structures to solve complex engineering challenges.
• Design efficient database schemas, caching strategies, and data access patterns for scalable applications.
• Establish engineering standards for code quality, testing, maintainability, and system performance.

2. AI Engineering & LLM Integration

• Architect and implement LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and agentic AI workflows.
• Develop solutions using vector databases, embeddings, semantic search, and prompt engineering.
• Build and optimize multi-agent systems, orchestration workflows, and tool integrations using frameworks such as LangChain and LlamaIndex.
• Implement Model Context Protocol (MCP) integrations where appropriate to connect AI systems with external tools and data sources.
• Evaluate model fine-tuning approaches and other techniques to improve AI performance where required.
• Establish LLMOps practices covering evaluation, observability, quality monitoring, and cost and latency optimization.

3. Cloud Infrastructure & Deployment

• Design and deploy cloud-native applications using AWS and GCP services.
• Build and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or similar tools.
• Containerize applications using Docker and support deployment and operations in Linux environments.
• Implement reliable asynchronous processing and messaging using queuing systems.
• Improve system availability, scalability, security, and deployment reliability across production environments.

4. Technical Leadership & Engineering Excellence

• Own technical decisions across complex backend and AI engineering initiatives.
• Guide engineers in architecture, implementation, debugging, code reviews, and engineering best practices.
• Identify performance bottlenecks and drive improvements in application reliability and scalability.
• Collaborate with product managers, frontend engineers, data scientists, and other stakeholders to deliver effective solutions.
• Evaluate emerging AI technologies, frameworks, and tools, adopting them when they provide meaningful technical or business value.
• Take ownership of features from technical design through implementation, deployment, and production support.

Required Technical Skills

Backend Development

• Strong Python programming expertise.
• Experience with Django, Flask, RESTful APIs, and WebSockets.
• Strong understanding of object-oriented programming, design patterns, algorithms, and data structures.

Databases & Performance

• Experience with PostgreSQL, MySQL, MongoDB, or equivalent database technologies.
• Strong understanding of relational database design, query optimization, and performance tuning.
• Experience implementing caching strategies and asynchronous processing.

Cloud & DevOps

• Hands-on experience with AWS and/or GCP.
• Experience with Git, Docker, Linux, and CI/CD pipelines.
• Familiarity with queuing systems and distributed application architectures.

System Design

• Ability to design secure, scalable, and maintainable backend systems.
• Experience making architecture decisions involving performance, reliability, scalability, and operational complexity.

Preferred AI/ML Skills

• Large Language Models (LLMs) and prompt engineering.
• Retrieval-Augmented Generation (RAG) architecture.
• Vector databases such as Pinecone, ChromaDB, or equivalent.
• Embeddings, semantic search, and retrieval optimization.
• Agentic AI workflows and multi-agent orchestration.
• Model Context Protocol (MCP) and tool integrations.
• LangChain, LlamaIndex, or similar frameworks.
• Model fine-tuning and LLMOps practices.
• AI evaluation frameworks, observability, and production quality monitoring.
• Experience optimizing inference costs, response latency, and AI application performance.

What We're Looking For

• Strong engineering fundamentals: You can solve complex technical problems and design maintainable systems.
• Hands-on ownership: You take responsibility for solutions from concept through production.
• System-level thinking: You understand how architecture, performance, security, and scalability work together.
• Practical AI expertise: You can build and deploy AI-powered applications beyond prototypes and proof of concepts.
• Technical leadership: You guide engineers, improve code quality, and establish sound engineering practices.
• Structured problem-solving: You make thoughtful technical decisions in ambiguous and fast-moving environments.
• Clear communication: You collaborate effectively across engineering and business teams.
• Continuous improvement: You stay current with evolving AI technologies and apply them where they create value.
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What We Offer

• Competitive compensation.
• Flexible work environment with Coimbatore office and hybrid options.
• Paid holidays and flexible time off.
• Medical insurance for self and family, with coverage of up to ₹4 lakhs per person.
• Opportunities to architect and build production-grade AI systems used by real customers.
• Exposure to global clients and technically challenging projects.
• A culture that values ownership, clarity, integrity, and continuous learning.

Skills

Python, Retrieval Augmented Generation (RAG), Artificial Intelligence (AI), Large Language Models (LLM) tuning, Vector database, Model Context Protocol (MCP), Anthropic Claude