Lead AI Engineer

About Techjays
Techjays is an AI-first technology company focused on building innovative, scalable, and production-ready AI solutions for global clients. We combine advanced AI capabilities with strong software engineering practices to solve real-world business challenges.
At Techjays, we believe in building beyond prototypes. We focus on delivering secure, reliable, and scalable AI-powered products that create measurable business impact.
Role Overview
We are looking for an experienced AI Lead Engineer to lead the design, development, and deployment of advanced AI applications. The ideal candidate will have strong backend engineering expertise, hands-on experience with Generative AI and Large Language Models (LLMs), and practical knowledge of Retrieval-Augmented Generation (RAG) and Agentic AI systems.
You will take ownership of AI solutions from architecture and development through deployment and optimization, while mentoring engineers and driving technical excellence across projects.
Key Responsibilities
Lead the architecture, design, development, and deployment of production-grade AI applications.
Build and optimize Generative AI solutions using LLMs, RAG pipelines, and Agentic AI frameworks.
Design scalable backend services, REST APIs, microservices, and AI-integrated applications using Python.
Develop document processing, semantic search, knowledge retrieval, and context-aware AI systems.
Work with vector databases and embedding models to build efficient retrieval pipelines.
Implement AI agents and multi-agent workflows using frameworks such as LangGraph and CrewAI.
Integrate AI models and services with existing enterprise applications, databases, and cloud platforms.
Make architectural decisions covering scalability, performance, security, reliability, and cost optimization.
Deploy, monitor, troubleshoot, and continuously improve AI solutions in production environments.
Establish best practices for coding standards, testing, CI/CD, observability, and AI application development.
Mentor engineers, conduct code reviews, and guide the team on technical decisions.
Collaborate with product managers, stakeholders, and cross-functional teams to translate business requirements into technical solutions.
Stay up to date with emerging AI technologies and identify opportunities to apply them to real-world business problems.
Required Technical Skills
Programming and Backend Engineering
Strong proficiency in Python and object-oriented programming.
Experience with FastAPI, Django, or Flask.
Strong understanding of REST APIs, microservices, asynchronous programming, and scalable system design.
Experience with SQL/NoSQL databases, caching, and data modeling.
Generative AI and LLMs
Hands-on experience building applications using LLMs and Generative AI.
Strong practical understanding of RAG architecture, chunking strategies, embeddings, retrieval, reranking, and prompt engineering.
Experience with vector databases such as Pinecone, FAISS, or equivalent technologies.
Experience building AI agents and agentic workflows using LangGraph, CrewAI, or similar frameworks.
Familiarity with LLM evaluation, hallucination reduction, context management, and production performance optimization.
Cloud and Deployment
Experience deploying AI applications on AWS or GCP.
Proficiency in Docker, Linux, Git, and CI/CD pipelines.
Understanding of application monitoring, logging, security, and production troubleshooting.
Knowledge of scalable, secure, and cost-efficient cloud architectures.
System Design and Leadership
Strong system design and architectural decision-making skills.
Experience leading technical projects and owning end-to-end solution delivery.
Ability to mentor engineers, review code, and drive engineering best practices.
Excellent problem-solving, communication, and stakeholder management skills.
What We’re Looking For
7–10+ years of experience in software engineering, backend development, AI engineering, or related roles.
Demonstrated experience delivering AI-powered applications into production.
Strong backend engineering fundamentals combined with practical Generative AI expertise.
Ability to explain architectural choices, trade-offs, and implementation decisions.
A hands-on technical leader who can guide a team while actively contributing to development.
Experience using AI development tools and coding assistants as part of everyday engineering workflows.
A strong ownership mindset, with the ability to independently solve complex technical problems.
What Success Looks Like
Delivering scalable, reliable, production-ready AI applications.
Building robust RAG and Agentic AI solutions beyond proof-of-concept implementations.
Improving system performance, response quality, reliability, and operational efficiency.
Enabling the engineering team through technical leadership, mentoring, and best practices.
Translating business requirements into measurable AI-driven outcomes.
Why Join Techjays?
Work on real-world AI products and enterprise-grade AI applications.
Collaborate with a team building AI-first solutions for global clients.
Take ownership of architecture, engineering decisions, and end-to-end delivery.
Work with emerging AI technologies and solve challenging technical problems.
Contribute to a culture that values innovation, accountability, and continuous learning.

Work arrangement
Hybrid