Principal, AI Engineer, Solution Delivery

• 8+ years of experience in Data Science, Machine Learning, and AI solution delivery.
• Strong hands-on experience designing and deploying Generative AI, Agentic AI, and traditional ML solutions.
• Deep expertise in LLMs, RAG architectures, prompt engineering, and retrieval systems.
• Experience building multi-agent AI solutions using frameworks such as LangGraph, Google ADK, AutoGen, CrewAI, or similar.
• Strong programming skills in Python with experience developing production-grade AI applications.
• Experience developing and deploying REST APIs, AI services, and intelligent applications.
• Hands-on experience with GCP Vertex AI, plus familiarity with AWS (Bedrock, SageMaker) and Databricks.
• Experience with Docker, Kubernetes, CI/CD, and cloud-based solution deployment.
• Strong understanding of AI evaluation, observability, hallucination detection, red-teaming, safety testing, and responsible AI practices.
• Experience integrating AI solutions with enterprise data platforms, APIs, tools, and business workflows.
• Proven ability to lead end-to-end AI solution delivery, from ideation and architecture through deployment and production monitoring.
• Strong stakeholder management, solution design, and technical leadership skills.
• Experience mentoring engineers and driving technical standards, best practices, and AI adoption across teams.
• Lead the design, development, and deployment of AI/ML, Generative AI, and Agentic AI solutions from concept through production.
• Architect and implement LLM-based applications, RAG frameworks, multi-agent systems, and intelligent automation solutions.
• Develop scalable AI services, APIs, and full-stack applications using Python, React, and modern cloud technologies.
• Build and optimize retrieval systems, knowledge graphs, prompt frameworks, and enterprise AI workflows.
• Partner with business stakeholders to identify opportunities, define solution roadmaps, and deliver measurable business outcomes.
• Drive technical decisions related to AI architecture, model selection, orchestration frameworks, cloud services, and data platform integrations.
• Develop rapid prototypes and proof-of-concepts to validate AI use cases and accelerate adoption.
• Establish and enforce best practices for AI engineering, model evaluation, testing, observability, security, and Responsible AI.
• Deploy, monitor, and optimize production AI solutions using cloud-native and DevOps practices.
• Collaborate with Data Scientists, Engineers, Product Managers, and Technology teams to deliver enterprise-scale AI capabilities.
• Mentor and guide AI Engineers and Data Scientists, fostering technical excellence and innovation.
• Evaluate emerging AI technologies, frameworks, and tools, and recommend their adoption where appropriate.
• Communicate solution architecture, implementation approaches, and business value to senior leadership and executive stakeholders.
• Drive continuous improvement of AI delivery standards, reusable frameworks, and enterprise AI capabilities.

Job Description

Must Have Technical/Functional Skills

• 8+ years of experience in Data Science, Machine Learning, and AI solution delivery.
• Strong hands-on experience designing and deploying Generative AI, Agentic AI, and traditional ML solutions.
• Deep expertise in LLMs, RAG architectures, prompt engineering, and retrieval systems.
• Experience building multi-agent AI solutions using frameworks such as LangGraph, Google ADK, AutoGen, CrewAI, or similar.
• Strong programming skills in Python with experience developing production-grade AI applications.
• Working knowledge of SQL, JavaScript/TypeScript, and React for full-stack AI solution development.
• Experience developing and deploying REST APIs, AI services, and intelligent applications.
• Hands-on experience with GCP Vertex AI, plus familiarity with AWS (Bedrock, SageMaker) and Databricks.
• Experience with Docker, Kubernetes, CI/CD, and cloud-based solution deployment.
• Strong understanding of AI evaluation, observability, hallucination detection, red-teaming, safety testing, and responsible AI practices.
• Experience integrating AI solutions with enterprise data platforms, APIs, tools, and business workflows.
• Proven ability to lead end-to-end AI solution delivery, from ideation and architecture through deployment and production monitoring.
• Strong stakeholder management, solution design, and technical leadership skills.
• Experience mentoring engineers and driving technical standards, best practices, and AI adoption across teams.

Roles & Responsibilities

• Lead the design, development, and deployment of AI/ML, Generative AI, and Agentic AI solutions from concept through production.
• Architect and implement LLM-based applications, RAG frameworks, multi-agent systems, and intelligent automation solutions.
• Develop scalable AI services, APIs, and full-stack applications using Python, React, and modern cloud technologies.
• Build and optimize retrieval systems, knowledge graphs, prompt frameworks, and enterprise AI workflows.
• Partner with business stakeholders to identify opportunities, define solution roadmaps, and deliver measurable business outcomes.
• Drive technical decisions related to AI architecture, model selection, orchestration frameworks, cloud services, and data platform integrations.
• Develop rapid prototypes and proof-of-concepts to validate AI use cases and accelerate adoption.
• Establish and enforce best practices for AI engineering, model evaluation, testing, observability, security, and Responsible AI.
• Deploy, monitor, and optimize production AI solutions using cloud-native and DevOps practices.
• Collaborate with Data Scientists, Engineers, Product Managers, and Technology teams to deliver enterprise-scale AI capabilities.
• Mentor and guide AI Engineers and Data Scientists, fostering technical excellence and innovation.
• Evaluate emerging AI technologies, frameworks, and tools, and recommend their adoption where appropriate.
• Communicate solution architecture, implementation approaches, and business value to senior leadership and executive stakeholders.
• Drive continuous improvement of AI delivery standards, reusable frameworks, and enterprise AI capabilities.

TCS Employee Benefits Summary

• Discret ionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
• Salary Range: $120,000 – 130,000 a year

Qualifications

BACHELOR OF COMPUTER SCIENCE