Senior AI engineer

Job Responsibilities

Responsible for designing, building, and maintaining scalable AI solutions

Develop and implement advanced Generative AI solutions (LLMs,

embeddings, retrieval techniques, prompt engineering)

Ensure that data architectures and infrastructure can scale seamlessly asthe data

volume and complexity grow

Lead, mentor, and develop a team of AI Engineers, fostering a collaborative and

inclusive team environment

Identify and address skill gaps, and provide opportunities for professional

development

Coordinate with stakeholders to gather requirements, set priorities, and define project

timelines

Ensure projects align with overall business objectives and data strategy

Ensure data quality, integrity, and security across all data engineering projects

Identify opportunities for process improvements and drive initiatives to enhance

the efficiency and effectiveness of data operations

Ability to build / drive reusable frameworks that can drive efficiency of the overall

data system

Manages conversation with the client stakeholders to understand the

requirement and translate it into technical outcomes

Internal Use Only

Required Skills (Must have)

Tech :

Experience of 5-7 years in development and deployment of scalable AI / ML

solutions

Has strong execution knowledge of Data Modeling, Databases in general (SQL and

NoSQL), software development lifecycle and practices, unit testing, functional

programming, etc

Develop and implement advanced Generative AI solutions (LLMs, embeddings,

retrieval techniques, prompt engineering)

Design and optimize Retrieval-Augmented Generation (RAG) solutions

Manage Databricks workflows, including job and cluster creation also Databricks

API

Apply data structures and algorithms knowledge, including multiprocessing and

optimization techniques

Utilize Python libraries (Pandas, Numpy, FastAPI) for data processing and API

development

Perform SQL optimization and database architecture design (schema creation,

normalization, functions, triggers)

Deploy and orchestrate AI models using Docker and Kubernetes

Collaborate using GitHub for version control and team collaboration

Work with cloud platforms for AI solution deployment and management

(Azure, GCP, AWS)

Utilize PySpark for data processing (optional)

Basic understanding of CI / CD pipelines and deployment process

Non-Tech :

Strong problem-solving skills with an ability to assess the financial impact of decisions,

both in running the delivery team and delivering solutions to clients

Proficient in written and verbal communication and able to hold conversations with mid

management-level clients

Ability to recognize pragmatic alternatives vis-à-vis a perfect solution and get the delivery

teams on board to pursue them, balancing time priorities with potential business impact

Strong people skills, including conflict resolution, empathy, communication, listening,

and negotiation

Shows proficiency in providing technical guidance and provide leadership and

mentorship to the delivery team

Self-driven with a strong sense of ownership