Technical Lead (AI ML)

SynapseIndia (Events); Dadri; On-site; INR 800,000 - 1,200,000; Full time

Job summary

SynapseIndia (Events) is seeking a Technical Lead (AI ML) with 6+ years of experience to architect end-to-end AI systems, including GenAI, LLMs, and RAG workflows. You will design scalable data pipelines, optimize performance and costs, and mentor junior engineers while collaborating with product and business teams.

The role requires expert Python, deep RAG architecture knowledge, and cloud platform experience (AWS/Azure/GCP) to build SaaS-based AI platforms and autonomous workflows.

Qualifications

• Expert-level Python programming; hands-on coding required.
• Deep expertise with LLMs, GenAI, RAG, and Agentic AI.
• Strong experience with vector databases, embeddings, and RAG architectures.
• Cloud platforms: AWS, Azure, or GCP.
• Understanding of SaaS-based architecture and distributed systems.
• Data engineering: scalable pipelines, embedding workflows.
• Experience with APIs, microservices, and system design.

Responsibilities

• Architect and build end-to-end AI systems (GenAI, LLMs, RAG, Agentic workflows).
• Design and optimize RAG pipelines (data ingestion → embeddings → retrieval).
• Lead development of Agentic AI systems and autonomous workflows.
• Architect SaaS-based, cloud-native AI platforms.
• Design scalable data pipelines (ETL/ELT, batch & streaming).
• Optimize performance, cost, and scalability of AI systems.
• Mentor junior engineers and drive engineering best practices.
• Collaborate with product and business teams for solution design.

Skills

Python

LLMs/GenAI

RAG architectures

Vector databases

Cloud platforms

SaaS architecture

Data pipelines

APIs/microservices

Job description

Designation: Technical Lead (AI ML)

Experience Range: 6+ years

What is the work?

• Architect and build end-to-end AI systems (GenAI, LLMs, RAG, Agentic workflows)
• Design and optimize RAG pipelines (data ingestion → embeddings → retrieval)
• Lead development of Agentic AI systems and autonomous workflows
• Architect SaaS‑based, cloud‑native AI platforms
• Design scalable data pipelines (ETL/ELT, batch & streaming)
• Optimize performance, cost, and scalability of AI systems
• Mentor junior engineers and drive engineering best practices
• Collaborate with product and business teams for solution design

What skills and experience are we looking for?

• Expert‑level Python (hands‑on coding is mandatory)
• Strong experience with LLMs, GenAI, RAG, and Agentic AI
• Mandatory: Deep expertise in vector databases, embeddings, and RAG architectures
• Strong experience with cloud platforms (AWS/Azure/GCP)
• Strong understanding of SaaS‑based architecture and distributed systems
• Strong data engineering expertise in designing scalable pipelines, Data preprocessing & embedding workflows
• Experience with APIs, microservices, and system design