We are seeking a Senior GenAI & ML Platform Engineer to help design, build, and scale next-generation AI and machine learning platform capabilities. This role will focus on expanding GenAI platform functionality, enabling multi-LLM orchestration, improving prompt lifecycle management, and supporting enterprise-grade ML data pipelines with strong security and governance standards.

The ideal candidate brings hands-on experience with TypeScript, Python, GenAI frameworks (LangChain), cloud-native platforms, and distributed systems, and is comfortable contributing to both AI-driven product innovation and data/ML platform reliability initiatives.

About First Factory

We are a software development company with over two decades of experience, boasting a dynamic team of 175+ professionals actively engaged in diverse projects across various industries. We invite you to join us on this journey as we thrive and embrace fresh challenges.

Key Responsibilities

GenAI Platform & Agent Systems

• Design and implement Prompt Catalog Management systems to support structured storage, retrieval, optimization, and reuse of prompts.

• Expand Agent Platform capabilities, including multi-LLM orchestration, workflow automation, and third-party system integrations.

• Build scalable services using TypeScript, Python, and LangChain to support AI-driven applications.

• Develop GenAI engagement features such as gamification elements, personalization logic, and user interaction tracking.

• Support migration from OpenAI to Amazon Bedrock, ensuring compatibility, scalability, and enterprise security compliance.

ML & Data Platform Engineering

• Contribute to the Data and ML Platform migration, ensuring stability, backward compatibility, and operational resilience.

• Build and maintain Golden ML Pipelines to standardize ingestion, processing, training, and deployment workflows.

• Implement best practices for ML lifecycle management, automation, and platform reliability.

• Support N-2 version compatibility across cloud services such as EMR Serverless, Lambda, and S3.

• Improve on-call readiness through documentation, incident playbooks, and operational runbooks.

Security, Governance & Reliability

• Embed data security, encryption, access control, and compliance monitoring across AI and ML pipelines.

• Apply governance standards to ensure secure handling of sensitive data and enterprise-grade platform operations.

• Monitor platform performance, troubleshoot failures, and improve observability and system reliability.

Collaboration & Engineering Excellence

• Partner with product, data, ML, and platform teams to align technical execution with business goals.

• Contribute to architecture decisions, system design discussions, and technical planning.

• Maintain clean, scalable, and well-documented codebases following best engineering practices.

• Support peer code reviews, knowledge sharing, and continuous improvement initiatives.

Requirements

• Strong experience with TypeScript and Python in production environments.

• Hands-on experience with GenAI technologies, LLM orchestration, and frameworks such as LangChain.

• Experience working with cloud-native architectures, preferably on AWS.

• Familiarity with Amazon Bedrock or similar managed AI platforms.

• Experience building ML pipelines, data workflows, or model deployment systems.

• Working knowledge of Java.

• Experience with serverless or cloud services such as Lambda, S3, and EMR Serverless.

• Strong understanding of distributed systems, APIs, and backend services.

• Experience implementing secure data pipelines, encryption, access controls, and compliance-aware workflows.

• Familiarity with ML lifecycle management, CI/CD, and automation pipelines.

• Experience supporting platform migrations, versioning strategies, and backward compatibility.

• Strong debugging, performance optimization, and reliability engineering skills.

• Strong problem-solving and system design capabilities.

• Ability to work across AI, ML, data, and platform engineering domains.

• Comfortable collaborating with cross-functional stakeholders in fast-paced environments.

• Excellent written and verbal English communication skills.

Nice to have

• Experience with multi-LLM orchestration or AI agent platforms.

• Experience with ML governance, model monitoring, or experiment tracking.

• Exposure to GenAI product features, such as personalization, gamification, or user engagement analytics.

• Experience working in enterprise-scale cloud or regulated environments.