Artificial Intelligence Engineer

Company Description

TalentBridge Global is a founder-led recruitment firm connecting exceptional professionals with world-class opportunities across IT and non-IT domains. The platform specializes in talent acquisition and placement to support the growth of businesses worldwide. With partnerships in technology and consulting, TalentBridge Global facilitates seamless deployment of skilled teams for global client engagements. The company is committed to fostering professional development and bridging gaps in the job market.

Role: Senior / Lead AI/ML Engineer

Location: Bangalore (Onsite)

Exp: 5+ yrs

Salary: 25 LPA

Np: Immediate

Role Description

This is a full-time, on-site role for an Artificial Intelligence ML Engineer located in Bengaluru.

We are looking for a Senior / Lead AI/ML Engineer to design, build, and optimize Model Context Protocol (MCP) servers, small language models (SLMs), and agentic AI workflows within an AWS-centric AI ecosystem. This role requires strong expertise in LLMs/SLMs, agent orchestration, data pipelines, Snowflake, and cloud-native AI deployments.

Key Responsibilities

Design and build MCP servers that consume and process:

Business requirements

Documentation

Configurations

Structured & unstructured data sources

Optimize and fine-tune Small Language Models (SLMs)

Build and enhance agentic / multi-agent workflows tailored to specific use cases

Support data traversal, transformations, and pipelines

Work with Snowflake-backed architectures

Implement hosting, deployment, and integration patterns

Contribute within an AWS-centric AI / ML ecosystem.

. Ensure performance, scalability, reliability, and cost optimization.

Key Contributions:

Designed and deployed MCP servers to process business requirements, technical documentation, configurations, and multi-source enterprise datasets

Built agentic AI workflows integrating MCP clients with LLM/SLM reasoning pipelines

Optimized Small Language Models (SLMs) for domain-specific tasks, achieving:

35% latency reduction

28% inference cost savings

Developed RAG pipelines leveraging Snowflake + Vector DB for contextual retrieval

Implemented AWS-based model hosting & serving architecture using:

SageMaker

ECS

Lambda

Led integration of AI services into existing AWS AI ecosystem

Technical Skills

Languages: Python, SQL

Frameworks: PyTorch, TensorFlow, LangChain

GenAI: LLMs, SLMs, RAG, Agentic AI, MCP

Cloud: AWS (SageMaker, Lambda, ECS, Bedrock)

Data: Snowflake, Databricks

DevOps: Docker, Kubernetes, CI/CD

Mandatory which is non negotiable:

Total Experience ~5+ yrs

LLM / GenAI Yes

MCP (Mandatory) Yes

Cloud (AWS/Azure) AWS

Containerization Docker

Scripting Python

AI Tools & Frameworks TensorFlow, LangChain

Snowflake or similar DWH Yes

Education

B.Tech Computer Science

[University Name]

Certifications

AWS Machine Learning Specialty

Generative AI / LLM Engineering

Drop resume at connect@talentbridgeglobal.in