Senior AI Engineer

Minimum 5 years' experience leading the design, development,

and deployment of scalable AI / ML and GenAI

solutions.

Key

Responsibilities

Architect and develop scalable GenAI pipelines, APIs, and

microservices for real-time and batch AI applications using

frameworks such as FastAPI, Ray, or

LangServe.

Design robust prompt

strategies for instruction-following, reasoning, and multi-turn

conversations, with a focus on RAG architectures for personalized,

domain-specific use cases.

Lead embedding

model selection and tuning to optimize semantic search and RAG

performance.

Oversee LLM Ops workflows,

including model orchestration, evaluation, deployment, rollback

strategies, and monitoring in production environments.

Drive model fine-tuning efforts to customize LLMs for

proprietary datasets and regulated industries.

Establish and govern AI testing frameworks, covering

functional testing, regression testing, hallucination detection,

safety filters, and output quality assessment.

Implement enterprise-grade observability, lineage

tracking, and CI / CD automation using tools such as

MLflow, Databricks, Azure ML, or Vertex

AI .

Lead continuous improvement

initiatives based on telemetry, user feedback, and cost-performance

trade-offs.

Demonstrate expertise in

Python , with deep proficiency in GenAI

frameworks, vector search systems, and MLOps

toolchains.

Qualifications

Minimum 5 years' experience architecting and deploying

scalable AI / ML and GenAI solutions in enterprise

environments.

Deep expertise in machine

learning, deep learning, and generative AI technologies, including

hands-on experience with frameworks like TensorFlow,

PyTorch , and modern LLM

orchestration tools.

Strong

familiarity with cloud platforms ( AWS, Azure,

GCP ) and MLOps practices for end-to-end machine

learning lifecycle management.

Demonstrated

leadership in managing agile, cross-functional teams and

collaborating with stakeholders.

Significant

experience in prompt engineering and prompt design for LLMs and

GenAI applications.

Bachelor's or Master's

degree in Computer Science, Data Science, Engineering, or a related

field; advanced degrees or certifications (e.g., Azure AI Engineer)

are advantageous.

Experience with

personalization, recommendation systems, or conversational AI is

highly desirable.