Senior AI engineer
4 weeks ago
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
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