RocketFrog.ai
Website:
rocketfrog.ai
Job details:
About Us
RocketFrog.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 Overview
We 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.
Location: Hybrid [Noida] - Experience: 8–12 Years
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
- B.Tech./M.Tech./Master's degree in Computer Science, IT, AI, Data Science, Mathematics, or a related discipline.
- 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.
Click on Apply to know more.
