Manager – Full Stack Development

Experience: 10 to 12 yearsTech Stack: Distributed Systems, AWS (incl. EKS), OpenShift, Automation (CI/CD & IaC), Go, Python, Node.js, AI-Assisted Software DevelopmentRole OverviewWe are looking for a Manager, Full Stack Development to provide strategic leadership across multiple engineering teams delivering complex, highly available, distributed systems on AWS using Go, Python, and Node.js on Kubernetes-based platforms such as EKS and OpenShift. You will own the engineering practice at the program or account level, combining deep technical authority with organizational leadership, executive stakeholder engagement, and responsibility for talent strategy, delivery excellence, and cross-team coordination. This is a senior leadership role for someone who can set a compelling technical vision, build high-performing teams, and be a trusted partner to client leadership and internal executives.Key ResponsibilitiesProvide strategic engineering leadership across multiple full stack development teams, setting direction, standards, and cultureOwn the architectural vision and technical roadmap for distributed systems programs on AWS, EKS, and OpenShiftDefine and govern engineering standards, coding practices, architectural patterns, and quality benchmarks at the practice levelLead AWS infrastructure strategy across programs, including cost optimization, security governance, resilience design, and platform evolutionDrive automation-first culture across CI/CD, infrastructure-as-code, testing, and operational practices at scaleBuild, grow, and retain a high-performing engineering organization; own workforce planning, hiring strategy, and senior talent developmentServe as the primary engineering executive for client stakeholders, building trusted relationships and driving strategic alignmentOwn program-level delivery commitments, escalation management, and risk mitigation across engagementsPartner with practice leads, account executives, and delivery leadership to shape proposals, scope engagements, and grow the accountEstablish and drive the AI-assisted engineering strategy across the practice, setting standards and governance for adoptionMentor and collaborate with Technical Leads and Engineers to drive delivery efficiency and Client satisfactionRepresent the engineering practice in internal leadership forums and contribute to organizational capability buildingRequired QualificationsBachelor's or Master's degree in Computer Science, Engineering, or a related field10-12 years of software engineering experience, including substantial depth in distributed systems and at least 5 years in engineering leadership rolesExpert-level proficiency in Go and Python, with strong working proficiency in Node.js for polyglot service environmentsDeep hands-on expertise with AWS architecture and services, including container orchestration on EKSHands-on experience running and operating workloads on Red Hat OpenShift as an enterprise Kubernetes platformExtensive experience designing and scaling automation frameworks and infrastructure-as-code (Terraform, CloudFormation, or Ansible) at the program levelMastery of distributed systems fundamentals: consistency models, fault tolerance, service mesh, messaging systems (Kafka, SQS/SNS), and data partitioningProven track record leading and scaling engineering organizations across multiple teams or accountsExecutive presence and communication skills -- experienced presenting to C-level client stakeholders and internal leadershipExperience with workforce planning, hiring, performance management, and organizational designTrack record of owning complex delivery programs, managing risk, and driving outcomes at the account or portfolio levelAI Knowledge & AI-Assisted Development (Required)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 documentationDefines and owns the organization-level strategy and governance for responsible AI-assisted coding, including validation rigor, security standards for AI-generated code, and data leakage prevention in promptsDeep practical knowledge of AI/LLM integration patterns for backend systems: APIs, prompt design, retrieval-augmented generation (RAG), embeddings, and agentic workflows (e.g., MCP)Drives AI adoption across the engineering practice to measurably improve velocity, code quality, and operational efficiency; builds the internal capability to sustain itOwns AI governance policy across the practice, ensuring alignment with enterprise data privacy, security, and compliance requirements -- including PHI and sensitive health plan dataPreferred QualificationsDeep domain expertise in the US health insurance or payer space: claims, enrollment, benefits, provider networks, and HIPAA/compliance-aware system design at the enterprise levelExperience with healthcare interoperability standards (HL7, FHIR, X12 EDI) applied across large-scale programsProven experience in a client-facing consulting or professional services environment at the delivery or account leadership levelExperience contributing to business development, RFP responses, or solution design for new or expanding client engagements