Associate Principal - Architecture

Evaluate market solutions and evolving platforms for AIML and assess fitment to client demands, ROI analysis readiness and develop enterprise recommendations.

Collaborate with business and technology teams in the design, prototyping, and selection of AIML solutions needed to deliver business value.

Continuous outside‑in scanning to facilitate continuous learning, hands‑on understanding, and adoption of AI Solutions Architecture industry standard methodologies and techniques.

Architect and help build enterprise solutions which include components across the Artificial Intelligence spectrum such as Machine Learning, generative AI, Deep Learning, Virtual Assistants, and Cognitive Services (e.g., Vision, Image, Textual, Language processing).

Assist in the development of roadmaps for AI, machine learning, and other advanced analytics areas (e.g., NLP, NLQ, LLMs, Agentic AI, MCP, A2A, Computer vision, ML platforms, open‑source libraries, event‑driven stream processing, data lakes).

Rapid Proof‑of‑Concept (PoC) Development: independently and quickly build functional prototypes and PoCs to test new AI models, algorithms, and approaches to solve specific business problems.

Model Experimentation: conduct hands‑on testing with various machine learning models, including fine tuning large language models (LLMs), training custom models and evaluating their performance using appropriate metrics.

Technical Validation: quickly set up and test new tools, APIs, and frameworks to validate their capabilities and suitability for large‑scale implementation.

Architectural Mentorship: offer support and mentorship to data science and engineering teams throughout the development, deployment, and operationalization of AI models.

System Integration Design: facilitate the integration of AIML models into existing enterprise applications, APIs, and business workflows.

See responsibilities above.

Have an excellent technical and commercial understanding in the creation of technology solutions and outcomes for customers.

Ability to learn emerging technologies and to apply these technologies to tackle business problems.

Strong desire to experiment with and learn new technologies and stay aligned with the latest community developments in AIML, Ops Engineering, and cloud‑native solutions.

Excellent written, verbal, and presentation communication skills; you will often find yourself in situations where you describe problem statements, solution options, your analysis and recommendations to a mix of technical and non‑technical stakeholders, using strong influencing skills to gain consensus and an agreed way forward.

Driven digital transformation roadmaps targeting operating models, cost reduction, and performance improvement.

Minimum bachelor’s degree qualification with a strong quantitative background (STEM education background; Science, Technology, Engineering, Mathematics), and/or an MBA preferred.

Deep knowledge of AIML tech across AWS, Azure, and GCP.

Understanding of cloud‑native services for data storage, compute, networking, and security.

Proven grasp of statistical concepts (e.g., hypothesis testing, probability distributions, regression analysis).

Experience with data exploration, feature engineering, and data preprocessing techniques.

Technical proficiency:

• 5 years of hands‑on AIML solution architecture, prototyping, and experimentation.
• 5 years of AWS/Azure data analytics and AI services.
• 3 years of hands‑on experience with data science tools and frameworks.
• Recent experience in Generative AI, Large Language Models (LLMs), Agentic AI platforms and solutions.

• Comprehensive Medical Plan covering Medical, Dental, Vision.
• Short‑Term and Long‑Term Disability Coverage.
• 401(k) Plan with Company match.
• Life Insurance.
• Vacation Time, Sick Leave, Paid Holidays.
• Paid Paternity and Maternity Leave.

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Individual pay is determined by work location, job level, and additional factors including job‑related skills, experience, and relevant education or training.

Disclaimer
:
The…