Senior Manager – Full Stack Development (AWS, Go/Python, Kubernetes & AI-Assisted Development)

Location: Remote

Experience: 12 to 15 years

Tech Stack: Distributed Systems, AWS (incl. EKS), OpenShift, Automation (CI/CD & IaC), Go, Python, Node.js, AI-Assisted Software Development

Role Overview

We are looking for a Senior 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 Responsibilities

        Provide strategic engineering leadership across multiple full stack development teams, setting direction, standards, and culture

        Own the architectural vision and technical roadmap for distributed systems programs on AWS, EKS, and OpenShift

        Define and govern engineering standards, coding practices, architectural patterns, and quality benchmarks at the practice level

        Lead AWS infrastructure strategy across programs, including cost optimization, security governance, resilience design, and platform evolution

        Drive automation-first culture across CI/CD, infrastructure-as-code, testing, and operational practices at scale

        Build, grow, and retain a high-performing engineering organization; own workforce planning, hiring strategy, and senior talent development

        Serve as the primary engineering executive for client stakeholders, building trusted relationships and driving strategic alignment

        Own program-level delivery commitments, escalation management, and risk mitigation across engagements

        Partner with practice leads, account executives, and delivery leadership to shape proposals, scope engagements, and grow the account

        Establish and drive the AI-assisted engineering strategy across the practice, setting standards and governance for adoption

        Mentor Managers and Technical Leads to drive delivery efficiency and governance

        Represent the engineering practice in internal leadership forums and contribute to organizational capability building

Required Qualifications

        Bachelor's or Master's degree in Computer Science, Engineering, or a related field

        12-15 years of software engineering experience, including substantial depth in distributed systems and at least 5 years in senior engineering leadership roles

        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

        Extensive experience designing and scaling automation frameworks and infrastructure-as-code (Terraform, CloudFormation, or Ansible) at the program level

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

        Proven track record leading and scaling engineering organizations across multiple teams or accounts

        Executive presence and communication skills -- experienced presenting to C-level client stakeholders and internal leadership

        Experience with workforce planning, senior hiring, performance management, and organizational design

        Track record of owning complex delivery programs, managing risk, and driving outcomes at the account or portfolio level

AI 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 documentation

        Defines 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 prompts

        Deep 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 it

        Owns AI governance policy across the practice, ensuring alignment with enterprise data privacy, security, and compliance requirements -- including PHI and sensitive health plan data

Preferred Qualifications

        Deep domain expertise in the US health insurance or payer space: claims, enrollment, benefits, provider networks, and HIPAA/compliance-aware system design at the enterprise level

        Experience with healthcare interoperability standards (HL7, FHIR, X12 EDI) applied across large-scale programs

        Proven experience in a client-facing consulting or professional services environment at the senior delivery or account leadership level

        Experience contributing to business development, RFP responses, or solution design for new or expanding client engagements