Technical Lead Fullstack

Role & responsibilities:

• Lead design and development of complex, distributed, high-availability systems in Go, Python, and Node.js
• Define technical approach and engineering best practices for the team
• Own key AWS infrastructure decisions covering scalability, cost, security, and resilience across container orchestration platforms (EKS, OpenShift) and serverless/compute services
• Drive automation strategy across CI/CD, infrastructure provisioning, testing, and operations
• Lead technical design reviews and set coding and architecture standards
• Mentor engineers and guide their technical growth
• Collaborating with senior leads to drive delivery efficiency and technology excellence
• Partner with product and business stakeholders to translate requirements into technical solutions
• Lead incident response, root-cause analysis, and long-term reliability improvements
• Evaluate and introduce new tools and technologies where they add clear value

Preferred candidate profile:

• Bachelors or masters degree in computer science, Engineering, or a related field

• 8–10 years of software engineering experience, with significant depth in distributed systems

• Expert-level proficiency in Go and Python, with strong working proficiency in Node.js for polyglot service environments

• Deep hands-on expertise with AWS architecture and services, including container orchestration on EKS

• Hands-on experience running and operating workloads on Red Hat OpenShift as an enterprise Kubernetes platform

• Proven experience designing and scaling automation frameworks and infrastructure-as-code (Terraform, CloudFormation, or Ansible)

• Strong grasp of distributed systems fundamentals: consistency models, fault tolerance, service mesh, messaging systems (Kafka, SQS/SNS), and data partitioning

• Experience leading technical projects or small teams

• Strong written and verbal communication skills for working with cross-functional and client stakeholders.

• Strong, demonstrated use of AI-assisted and agentic development workflows (Claude Code, Copilot, Cursor, or similar) across the full development lifecycle: design, coding, testing, review, and documentation

• Able to define and enforce team-level standards for responsible AI-assisted coding, including validation rigor, security scanning of AI-generated code, and avoiding data leakage in prompts

• Practical knowledge of AI/LLM integration patterns for backend systems: APIs, prompt design, retrieval-augmented generation (RAG), embeddings, and agentic workflows (e.g., MCP)

• Able to identify where AI-driven automation can meaningfully improve engineering velocity, code quality, or operational efficiency, and lead adoption within the team

• Ensures AI tool usage on the team aligns with data privacy and security requirements, particularly around PHI and other sensitive health plan data