Description

Responsibilities

• Drive spec-first development practices across teams — leading the authoring of specs, technical plans, and agent-ready task breakdowns using GitHub Spec Kit or equivalent tooling before any code is written.

• Architect and build full stack web applications using React and modern JavaScript / TypeScript frameworks on the frontend, backed by Node.js and Python services.

• Design, develop, and maintain RESTful and GraphQL APIs — ensuring performance, reliability, versioning, and security across all service boundaries.

• Lead cloud architecture and deployment on AWS, leveraging services such as Lambda, EC2, S3, API Gateway, RDS, and CloudFormation for scalable, resilient systems.

• Integrate and build AI-powered features using LLMs, AI agents, and prompt engineering techniques, translating GenAI capabilities into tangible product value.

• Own data architecture decisions across MongoDB and PostgreSQL, including schema design, indexing strategies, query optimization, and migrations.

• Mentor and technically guide engineers at all levels, conducting code reviews and raising the overall engineering bar across the organization.

• Partner with product, design, and AI/ML teams to define requirements and translate them into well-specified, high-quality software.

• Contribute to engineering strategy, tooling choices, and cross-team standards as a senior technical leader.

Required Qualifications

• 12+ years of professional software engineering experience with a strong full stack background.

• Proven experience with GenAI tools and a spec-first development approach — including GitHub Spec Kit, AI agent frameworks, or equivalent spec-driven methodologies.

• Expert-level proficiency in React and modern JavaScript / TypeScript frameworks (Next.js, Vue, or similar).

• Strong backend development experience with both Node.js and Python — building, maintaining, and scaling production-grade REST and GraphQL APIs.

• Deep, hands-on experience with AWS — comfortable across core services (Lambda, EC2, S3, API Gateway, RDS) as well as security, networking, and cost optimization.

• Solid experience designing and managing both MongoDB (document store) and PostgreSQL (relational) databases at scale.

• Demonstrated ability to integrate LLM APIs (OpenAI, Anthropic, or similar), build prompt engineering pipelines, and deliver AI-augmented product features.

• Track record of leading technical delivery — setting architecture direction, unblocking teams, and owning outcomes across complex, multi-service systems.

• Bachelor’s or master’s degree in computer science, Engineering, or equivalent practical experience.

Good to Have

• Experience with GitHub Copilot, Cursor, or AI-assisted development environments integrated into day-to-day engineering workflows.

• Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code tools (Terraform, AWS CDK).

• Exposure to vector databases (Pinecone, pgvector) or RAG (Retrieval-Augmented Generation) pipeline design.

• Experience with AI orchestration frameworks such as LangChain or LlamaIndex.

• Knowledge of event-driven architecture patterns using AWS SQS, SNS, or EventBridge.

• Familiarity with MLOps practices and deploying ML models into production pipelines.

• Contributions to open-source projects, technical writing, or a portfolio of AI-integrated applications.

Years of Experience: 8.00 Years of Experience

Key Skills

Education

Bachelor's degree