Designation: Senior AI Platform Engineer

Location: Hybrid

Responsibilities (The "AI Platform" Mindset)

• Centralized Orchestration: Design and implement a robust engineering foundation to host all AI agents and models within Amazon Bedrock, ensuring they are governed, scalable, and deployable across various product lines.

• Platform over Projects: Move the team away from bespoke, manual model deployments toward a standardized AI Platform model. Build "Internal AI Services" and tools to empower underserved functions like Sales, Legal, Finance, and Accounting.

• CI/CD & DataOps: Establish automated MLOps pipelines for model training, evaluation, and deployment. Partner with Data Engineering to ensure "DataOps" readiness for high-performance AI features.

• Augmentation & Governance: Work with our business and product teams to build human-in-the-loop (HITL) workflows that augment, not automate, ensuring all AI features are safe, transparent, and compliant.

• Operational Excellence: Optimize and scale machine learning infrastructure (AWS/Kubernetes) to support high-performance model training and inference while reducing the "operational debt" of existing GenAI/ML models.

Qualifications

Must Have

• 5-7 years of software engineering experience with strong system design skills

• 2-3 years building and operating production LLM systems, including RAG or agent workflows

• Led the design and delivery of at least one end-to-end GenAI system from ideation to production

• Deep expertise in building AI agents, specifically managing state, long-term memory, and multi-turn context

• Hands-on experience with LLM integration, prompt engineering, structured outputs, and evaluation frameworks, including proficiency with orchestration tools like LangChain and/or LangGraph.

• Have built APIs or internal platforms that expose AI capabilities to multiple teams with cost and latency optimization

• Strong understanding of CI/CD, Infrastructure as Code, and distributed system design to support scalable AI platforms

• Proficient in Python and at least one additional language such as TypeScript

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field

Nice to Have

• Experience with AWS, including Bedrock and related AI services

• Experience with Docker and Kubernetes-based deployments

• Experience with microservices or cloud-native architectures

• Hands-on experience with ETL processes, data pipelines, and data warehousing solutions

• Experience building AI systems in regulated or compliance-driven domains