Senior AI / ML Engineer – Agentic AI

About the Role

We are looking for a

highly skilled and innovative AI / ML Engineer (Contract role)

to join our

Agentic AI and Generative AI (GenAI)

development team. The ideal candidate will be hands-on in building and optimizing

Multimodal RAG architectures, intelligent agents, and enterprise-grade GenAI automation systems .

This role offers a unique opportunity to work on next-generation

Agentic AI frameworks , combining

LLMs, multimodal retrieval, and automation pipelines

for global enterprise use cases.

Key Responsibilities

Design, build, and deploy

Multimodal RAG architectures

and

LangGraph-based Agentic AI systems

for enterprise automation.

Develop and optimize

chunking strategies, embedding pipelines , and

vector database integrations

(Vertex AI, PGVector, Pinecone).

Integrate

LLMs (Gemini 2.5, Gemma, LLaMA 4, etc.)

into GenAI workflows and automation pipelines.

Implement and maintain

CI / CD pipelines , supporting

MLOps / LLMOps

frameworks for continuous delivery.

Collaborate with cross-functional teams to ensure

scalable deployment

on

GCP (Vertex AI)

platforms.

Continuously evaluate, monitor, and fine-tune models for

precision, recall, relevance, faithfulness , and

cost efficiency .

Contribute to the development of

evaluation frameworks (e.g., RAGAS)

and

AI efficacy dashboards.

Required Skills & Experience

Minimum

4+ years of experience

in

AI / ML model development

with a focus on

GenAI, RAG, or Agentic AI

systems.

Proven hands-on experience with :

Vector databases :

PGVector, Pinecone, or similar

Multimodal data processing :

text, image, audio embeddings and chunking

Embedding models

and

vector search optimization

Practical knowledge of

LangChain, LangGraph , and

LLMOps

toolkits.

Familiarity with

GCP Vertex AI

or equivalent ML platforms.

Experience with

CI / CD ,

MLflow , or other MLOps automation pipelines.

Exposure to

prompt engineering, fine-tuning , and

LLM model integration .

Good to Have

Bachelor’s or Master’s degree in

Computer Science, AI / ML, Data Science , or related disciplines.

GCP / AWS / ML certifications

are an advantage.

Contributions to

open-source AI projects

or publications in

GenAI / RAG / Agentic AI

domains.

Strong problem-solving ability and a mindset for

rapid prototyping and experimentation .