Staff Software Development Engineer – Enterprise AI Infrastructure

Jobtailor

California (MO)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

Jobtailor is building an enterprise AI platform on AWS, designed to scale with EKS, Bedrock, and OpenSearch while enforcing strict security, governance, and regulatory compliance. You will architect and lead the development of autonomous agent workflows and multi-agent systems, ensuring robust integrations with internal and third-party SaaS tools.

The role requires deep cloud and AI infra expertise, leadership, and the ability to mentor teams as we advance platform evolution and governance.

Qualifications

Bachelor’s degree or equivalent in CS/SE/AI; advanced degrees preferred.
8–12 years of software development and cloud infra with leadership.
Deep AWS/EKS architecture, Kubernetes networking, VPC/PrivateLink, IAM, KMS, Bedrock.
Experience in agentic AI development and LLM tool-calling workflows.
Experience with MCP integrations and secure API/tool integrations for LLMs.
Strong IAM, OAuth, JWT, and IdP integrations (Okta/Auth0).
Proficiency in Python, TypeScript, or Go; IaC (Terraform, AWS CDK).
Knowledge of vector DBs, RAG, and access controls (OpenSearch, FAISS, pgvector).
Experience with CI/CD, MLOps, Helm, and observability stacks.

Responsibilities

Lead end-to-end design, development, deployment, and monitoring of an enterprise AI platform on AWS.
Design and implement agentic AI workflows and multi-agent systems with LLM orchestration.
Architect secure integrations using MCP to connect with internal systems and SaaS apps.
Implement zero-trust, token-based authorization and Cedar policy enforcement.
Develop containerized runtimes (Kubernetes on EKS) for secure AI model execution.
Maintain audit trails and observability with CloudTrail, OpenTelemetry, and related tools.
Collaborate with Product, Security, Regulatory, and stakeholders for compliant infra.
Troubleshoot cloud infra, Kubernetes networking, PrivateLink, and workflow issues.
Contribute to AI infra roadmaps, IaC practices, and platform evolution.
Mentor engineers and promote engineering excellence and security.
Work with Compliance functions to meet regulatory requirements.

Skills

Problem-Solving

Leadership

Communication

Mentoring

Strategic Thinking

Education

Bachelor's Degree

Master's Degree

PhD

Tools

Amazon EKS

Kubernetes

Python

TypeScript

Terraform

AWS CDK

Model Context Protocol

Deterministic Policy Enforcement

CI/CD Pipelines

Job description

• Lead the end-to-end design, development, deployment, and monitoring of a scalable, governed enterprise AI platform leveraging Amazon EKS and AWS native services (e.g., Bedrock, OpenSearch Serverless, KMS, VPC).
• Design and implement agentic AI workflows, specialized autonomous agents, and multi-agent systems using advanced LLM orchestration techniques and agent frameworks.
• Architect and manage secure integrations using the Model Context Protocol (MCP) to connect the AI platform with internal systems, vector databases, and third-party SaaS applications (e.g., Google Workspace, Slack).
• Build and enforce strict identity, authorization, and zero-trust token brokering flows leveraging Okta, Auth0, and custom JWT authorizers to ensure secure, least-privilege tool execution.
• Implement deterministic policy controls (e.g., Cedar policy engine) to enforce role-based access, approval gates, and human-in-the-loop checks at the API gateway level.
• Develop and maintain highly isolated, scalable containerized runtime environments (e.g., Kubernetes pods on Amazon EKS) for secure AI model execution, tool usage, and knowledge retrieval.
• Establish and maintain comprehensive audit trails and observability for all AI interactions, utilizing AWS CloudTrail and GenAI observability tools (e.g., OpenTelemetry) to track cost, latency, and tool calls.
• Collaborate with Product Management, Security, Regulatory, and business stakeholders to translate enterprise requirements into scalable, compliant AI infrastructure solutions.
• Troubleshoot and resolve complex technical issues involving cloud infrastructure, Kubernetes networking, network isolation (PrivateLink), and agentic workflows.
• Contribute to technology roadmaps, AI infrastructure strategy, and long-term platform evolution initiatives.
• Mentor engineers, software developers, and technical teams while promoting engineering excellence, infrastructure-as-code (IaC) best practices, and continuous improvement.
• Partner with Quality, Regulatory, Privacy, Security, and Compliance functions to ensure software and AI systems operate in accordance with applicable regulatory requirements and company policies.

Requirements

Bachelor's degree or equivalent in Computer Science, Software Engineering, Artificial Intelligence, Cloud Computing, or related field; Master's or PhD preferred.
8-12 years of relevant software development and cloud infrastructure experience with demonstrated technical leadership.
Deep expertise in AWS cloud architecture and container orchestration, specifically with Amazon EKS, Kubernetes networking, network isolation (VPC, PrivateLink), IAM, KMS, and GenAI services (e.g., AWS Bedrock).
Proven experience in agentic AI development, building autonomous agents, and orchestrating LLM tool-calling workflows using frameworks like LangChain, LangGraph, AutoGen, or Claude Agent SDK.
Hands-on experience implementing the Model Context Protocol (MCP) or building robust, governed API/tool integrations for LLMs.
Strong background in identity and access management (IAM), OAuth, JWT, and integrating with enterprise IdPs (Okta, Auth0) for scoped, token-based authorization.
Advanced proficiency in programming languages such as Python, TypeScript, or Go, and infrastructure-as-code tools (Terraform, AWS CDK).
Experience with vector databases, RAG (Retrieval-Augmented Generation) architectures, and row-level access controls (e.g., OpenSearch, FAISS, pgvector).
Proficiency with CI/CD pipelines, MLOps practices, Kubernetes ecosystem tools (e.g., Helm), containerization, and modern observability stacks.
Demonstrated level of knowledge regarding applicable regulatory standards commensurate with the position's complexity and scope, contributing to organizational regulatory compliance. Minimal applicable standards for this position include:
Cybersecurity principles, tools, and control frameworks (e.g., ISO 27001, NIST, SOC 2, HIPAA)
Operations within the regulated medical device environment (e.g., IVDD, IVDR, FDA 21 CFR 800 series, FDA 21 CFR Part 11)
AI governance, software validation, data integrity, and risk management principles applicable to regulated environments
Deep expertise in cloud infrastructure, containerized environments, agentic artificial intelligence, and secure distributed system design.
Exceptional problem-solving and analytical skills with the ability to address ambiguous, high-impact technical challenges in AI orchestration and Kubernetes scaling.
Strong leadership and influence skills, capable of driving alignment across engineering, security, regulatory, and business stakeholders.
Excellent communication skills with the ability to explain complex LLM behaviors, infrastructure architectures, and security boundaries to technical and non-technical audiences.
Proven mentoring and coaching capabilities that elevate cloud engineering and AI talent.
Strong understanding of AI safety, prompt injection defenses, secure tool execution, and deterministic policy enforcement.
Strategic thinking with the ability to balance long-term enterprise AI platform vision with near-term business delivery.
High adaptability and intellectual curiosity regarding emerging agentic AI frameworks, MCP specifications, and cloud computing trends.

Core Competencies

Demonstrates expertise in AWS Cloud Architecture, Container Orchestration, and Agentic AI Development, with a strong focus on secure integrations and compliance within regulated environments. Proven ability to lead technical teams, mentor engineers, and drive strategic AI platform initiatives.

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