Senior AI Engineer

TheMathCompany or MathCo® is a global Enterprise AI and Analytics company trusted for data-driven decision-making by leading Fortune 500 and Global 2000 enterprises. Founded in 2016, MathCo builds custom AI and advanced analytics solutions focused on enterprise problem-solving through its innovative hybrid model. NucliOS, MathCo’s proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. For our employees, we foster an open, transparent, and collaborative culture with no barriers, making MathCo a great place to work. We provide exciting growth opportunities, value capabilities, and attitude over experience, enabling the Mathemagicians to ‘Leave a Mark’.

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 as the 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

Required Skills (Must have)

Tech :

Experience of 4.5 - 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

Good to Have Skills

Familiarity with data visualization tools and techniques

Knowledge of data security and privacy practices

Understanding of data governance and compliance frameworks

Experience with graph databases and graph processing frameworks

Experience with data virtualization and data federation techniques

Proficiency in data profiling and data quality management