Tech Lead - Agentic AI
RocketFrog.ai
Noida, Uttar Pradesh, India
Tech Lead – Agentic AI and SystemsLocation: Hybrid [Noida]
Experience: 8–12 Years
About UsRocketFrog.ai is an AI Studio for Business, delivering AI-driven solutions across Healthcare, Pharma, BFSI, Hi-Tech, and Consumer Services. We specialize in Agentic AI, Machine Learning, Data Engineering, and AI-first Product Development to create real business impact.
Role OverviewWe are looking for a Tech Lead who can design and lead the development of modern AI-native enterprise systems.
The ideal candidate should combine strong System Design and Solution Architecture skills with a good understanding of Agentic AI, LLMs, Full Stack Development, data platforms, Knowledge Graphs, Cloud, and AI/ML fundamentals.
The person should also be comfortable using AI-driven development tools to improve engineering productivity and guide teams in modern software development practices.
Key Responsibilities
- Lead Technical Delivery: Own end-to-end technical delivery across application engineering, Agentic AI/ML integration, data platforms, enterprise integrations, cloud deployment, and production support.
- Design Scalable Architecture: Define system architecture, API contracts, data flows, database schemas, service boundaries, integration patterns, and technology choices.
- Translate Business Problems into Technical Solutions: Work with business and product teams to understand requirements and convert them into practical, scalable technical designs.
- Lead Client Technical Discussions: Interact directly with American / European clients, understand their business and technical requirements, explain solution approaches, discuss trade-offs, and drive technical decisions.
- Design Agentic AI Solutions: Architect intelligent workflows involving AI agents, LLMs, RAG, tools, orchestration, MCP/A2A, and enterprise systems.
- Lead AI-Driven Development: Guide teams in effectively using modern AI development tools such as Claude Code, Codex, GitHub Copilot, or equivalent for software design, development, testing, and engineering productivity.
- Design Data & Knowledge Platforms: Design data workflows using Apache Airflow, Knowledge Graphs using Neo4j, and appropriate enterprise data architectures.
- Lead Application Engineering: Guide the development of web applications, backend services, APIs, workflows, dashboards, and data-driven user experiences.
- Integrate Enterprise Systems: Design integrations with ERP, CRM, Master Data Management, inventory, order management, warehouse, production, or other enterprise platforms.
- Ensure Production Readiness: Own performance, scalability, security, observability, fault tolerance, CI/CD, cloud infrastructure, and deployment readiness.
- Guide Engineering Teams: Mentor developers, review code and technical designs, resolve technical blockers, and ensure architectural alignment across the team.
Required Skills & Expertise
- Agentic AI: Strong understanding of AI agents, tool use, orchestration, multi-agent systems, RAG, MCP/A2A concepts, and agentic workflows.
- AI-Driven Development: Hands-on experience with modern AI-assisted development tools such as Claude Code, Codex, GitHub Copilot, or equivalent.
- Large Language Models: Strong understanding of LLM fundamentals and production usage, including Transformers, attention, embeddings, tokenization, context windows, reasoning models, prompt/KV caching, structured outputs, tool calling, RAG, model routing, latency/cost trade-offs, and model limitations.
- Full Stack Fundamentals: Working knowledge of modern web application development, including frontend, backend, APIs, databases, authentication, and web application architecture.
- Knowledge Graphs: Experience with Neo4j, graph data modelling, and Cypher.
- System Design & Solution Architecture: Strong ability to design scalable, modular, production-grade enterprise systems.
- Master Data Management: Good understanding of MDM concepts, including master and reference data, golden records, entity resolution, matching, deduplication, data quality, governance, and master-data integration. Hands-on experience with an enterprise MDM platform is good to have.
- Apache Airflow: Hands-on experience designing and managing workflow and data orchestration pipelines.
- Cloud & Deployment: Strong working knowledge of cloud architecture, preferably AWS, including EC2, ECS, EKS, VPC, IAM, S3, Load Balancers, CloudWatch, and managed databases. Experience deploying AI/LLM workloads using platforms such as AWS Bedrock or Azure OpenAI. Good understanding of Docker, Kubernetes, CI/CD, security, scalability, observability, and production deployment.
- AI/ML Mathematical Foundation: Good understanding of probability, statistics, linear algebra, optimization, and core Machine Learning concepts.
- Programming: Strong programming ability, preferably in Python, with the ability to understand, review, and guide production-quality code.
Required Background
- Master’s degree in AI / ML / Data Science; or a B.Tech. with a strong foundation in mathematics, probability, statistics, linear algebra, and machine learning.
- 8–12 years of software, AI, data, or platform engineering experience.
- Experience in a Tech Lead, Solution Architect, or similar technical leadership role.
- Experience leading engineering teams and owning technical delivery of production systems.
- Experience working on Financial Services, Capital Markets, FinTech, or investment-related technology solutions is preferred.
Why Join RocketFrog.ai?
- Build next-generation Agentic AI and AI-native enterprise systems.
- Work across AI, Knowledge Graphs, data platforms, cloud, and modern application development.
- Use AI-driven engineering practices to rethink how software is designed, developed, and tested.
- Work directly with global clients on challenging real-world business problems.
- Be part of the growth journey of RocketFrog.ai.If you enjoy connecting AI, data, cloud, architecture, and software engineering to build modern intelligent systems, we would love to talk.