AWS AI Senior Tech Lead

SFE; United States; Remote; USD 190,000 - 270,000; Full time

Job summary

SFE is seeking an AWS AI Senior Tech Lead to drive delivery of AI agent capabilities in a remote, full-time capacity. You will shape cloud-native solutions, mentor teams, and ensure secure, scalable architectures for enterprise-grade AI platforms.

You will collaborate with security, data, and enterprise teams to align with client standards and deliver robust, observable systems with strong governance and risk controls.

Qualifications

• Bachelor's degree in CS/Engineering or related field required.
• 10+ years technology architecture experience preferred.
• Strong leadership and stakeholder communication skills required.
• Hands-on AWS experience with Bedrock, SageMaker, Lambda, Step Functions, and CI/CD tooling expected.

Responsibilities

• Lead the delivery of AI agent capabilities and platform components.
• Translate architecture into engineering designs and sprint plans.
• Guide teams on AI patterns, secure coding, and performance optimization.
• Build and review core components: agent orchestration, API layers, RAG services.
• Coordinate with architects, product owners, security SMEs, and QA for end-to-end quality.
• Establish best practices, coding standards, and reusable accelerators.
• Support environment readiness, deployment planning, and production readiness.

Skills

AWS Certified

Python

TypeScript/JS

REST APIs

Microservices

Event-driven

Containerized

Bedrock/SageMaker

Prompt engineering

Security practices

Leadership

Compliance & risk

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

IAM

CloudWatch

API Gateway

Job description

Role: AWS AI Senior Tech Lead
Location: Remote
Term: Full Time

Job Description

Must Have Technical/Functional Skills

• AWS Certified Solutions Architect Professional or equivalent cloud architecture certification preferred.
• Strong hands-on capability in Python, TypeScript/JavaScript, REST APIs, microservices, event-driven patterns, and containerized deployments.
• Experience with AWS Bedrock, SageMaker, Lambda, Step Functions, ECS/EKS, API Gateway, S3, CloudWatch, and CI/CD tooling.
• Deep understanding of prompt engineering, agent orchestration, tool integration, vector stores, embeddings, model evaluation, and AI guardrails.
• Ability to enforce engineering standards, code quality, secure coding, performance tuning, and observability practices.
• Strong leadership, mentoring, estimation, planning, and stakeholder communication skills.
• Familiarity with compliance, audit logging, model risk controls, and responsible AI practices.
• Strong understanding of AI agent patterns, prompt orchestration, tool/function calling, RAG pipelines, model evaluation, guardrails, and observability.
• Strong application security and cloud security knowledge, including threat modeling, OWASP/API security, identity and access management, encryption, secure SDLC, logging, monitoring, and resilience patterns.
• Ability to define non-functional requirements for security, privacy, performance, resiliency, scalability, auditability, and operational readiness.
• Excellent communication skills with ability to present architecture decisions, risks, and trade-offs to senior stakeholders.

Roles & Responsibilities

• Lead the technical delivery of AI agent capabilities, reusable platform components, integrations, and automation workflows.
• Translate solution architecture into detailed engineering designs, sprint plans, and implementation tasks.
• Guide developers on AI patterns, cloud-native implementation, secure coding, testability, and performance optimization.
• Build and review core components such as agent orchestration services, API layers, RAG services, tool connectors, and model interaction modules.
• Coordinate with architects, product owners, UX designers, security SMEs, and QA teams to drive end-to-end delivery quality.
• Establish technical best practices, coding standards, review processes, and reusable accelerators.
• Support environment readiness, deployment planning, defect triage, production readiness reviews, and knowledge transition.
• Collaborate with enterprise architecture, security, data, cloud platform, application, and business teams to ensure alignment with client standards.
• Embed application security and cloud security requirements into solution design, including IAM, encryption, network controls, API protection, secrets management, secure data access, logging, and monitoring.
• Drive build-versus-buy evaluations, technology selection, platform design decisions, security trade-off analysis, and architectural risk mitigation.
• Establish reusable cloud patterns, secure integration standards, deployment approaches, and non-functional requirements for performance, resiliency, and security.
• Review detailed designs and implementation outputs to ensure adherence to approved architecture, security controls, and operational readiness expectations.

Generic Managerial Skills, If any

• Bachelor's degree in computer science, Engineering, Informatio n Systems, Cybersecurity, or related field; advanced degree preferred.
• 10+ years of technology architecture experience, including 4+ years designing cloud-native solutions on AWS.
• Strong experience architecting Gen AI, LLM, RAG, agentic workflow, and AI platform solutions for enterprise-scale programs.
• Hands‑on exposure to AWS Bedrock, SageMaker, Lambda, Step Functions, API Gateway, ECS/EKS, S3, IAM, CloudWatch, networking, and security constructs.
• Strong understanding of application security and cloud security, including secure design, IAM, encryption, network segmentation, API security, secrets management, logging, monitoring, and compliance controls.
• Experience designing governed, compliant, auditable platforms for regulated domains; insurance or financial services experience preferred.