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