Lead Software Engineer – GenAI-Assisted, Autonomous Engineering

Jobtailor

Iowa (LA)

On-site

USD 120,000 - 180,000

Full time

5 days ago

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Job summary

Jobtailor is seeking an experienced software engineering leader in the United States to drive AI-assisted and autonomous engineering initiatives across the organization. You will guide design, development, and deployment of GenAI-enabled platforms, mentor teams, and promote best practices for AI-powered development while ensuring governance and compliance.

Responsibilities include scaling AI tooling like Copilot and Claude Code, integrating GenAI into SDLCs, and delivering measurable outcomes

Qualifications

5+ years of Software Engineering experience
5+ years of experience developing enterprise applications using Java, Python, or comparable technologies
1+ years of experience with AI-assisted/autonomous software engineering platforms such as GitHub Copilot, Devin, Claude Code, Cursor, or similar technologies
1+ years of experience building and deploying AI-powered applications using LLMs and Generative AI technologies
Experience designing and implementing distributed systems, APIs, microservices, and event‑driven architectures
Hands‑on experience with CI/CD pipelines, source control platforms, developer tooling, and software engineering best practices
Experience working with cloud‑native technologies and containerized platforms
Strong technical leadership, problem‑solving, and collaboration skills
Experience with enablement and training of AI platforms such as GitHub Copilot, Devin, Claude Code, Cursor, or similar technologies
Strong knowledge of Agentic AI, Retrieval‑Augmented Generation (RAG), Fine‑Tuning, prompt engineering, multi‑agent architectures, and MCP integrations
Experience developing scalable AI platforms and engineering enablement solutions
Experience with software engineering analytics, developer productivity measurement, and outcome‑based reporting
Knowledge of GenAI FinOps, technology cost management, and value realization frameworks
Experience working in highly regulated enterprise environments with governance, security, and compliance requirements
Not eligible for Visa sponsorship

Responsibilities

Lead the design, development, integration, and deployment of enterprise AI-assisted and autonomous engineering solutions
Provide technical leadership for the rollout and scaling of AI platforms across CDXO and Lines of Business
Build and integrate GenAI capabilities into enterprise SDLC workflows, CI/CD pipelines, and developer toolchains
Design and develop reusable engineering services, accelerators, frameworks, and enterprise capabilities
Collaborate with product owners, engineering teams, and platform organizations to improve the software development lifecycle with Generative AI
Lead developer onboarding, technical enablement, and adoption efforts while establishing best practices for prompt engineering
Design, implement, and operationalize solutions leveraging multi-agent systems and AI orchestration patterns
Monitor platform adoption, performance, and business outcomes
Develop metrics, dashboards, and reporting frameworks for GenAI FinOps initiatives
Provide hands‑on troubleshooting and guidance to engineering teams
Align solutions with enterprise architecture, security, governance, and Responsible AI requirements
Contribute to InnerSource initiatives and reusable enterprise capabilities
Collaborate with experts and industry groups to resolve complex issues
Lead projects, teams, or serve as a peer mentor

Skills

Software Engineering

Java Development

Python Development

Technical Leadership

Problem-Solving

Collaboration

CI/CD Pipeline Implementation

Cloud-Native Technologies

Containerized Platforms

Governance & Compliance

Tools

GitHub Copilot

Devin

Claude Code

Cursor

LLMs

Agentic AI

MCP Integrations

Prompt Engineering

Multi-Agent Architectures

GenAI FinOps

Job description

Responsibilities

Lead the design, development, integration, and deployment of enterprise AI-assisted and autonomous engineering solutions
Provide technical leadership for the rollout and scaling of GitHub Copilot, Devin, Claude Code, Cursor, and future AI engineering platforms across CDXO and Lines of Business
Build and integrate GenAI capabilities into enterprise SDLC workflows, CI/CD pipelines, developer platforms, repositories, APIs, and engineering toolchains
Design and develop reusable engineering services, accelerators, frameworks, and enterprise capabilities that improve software delivery efficiency
Partner with product owners, engineering teams, and platform organizations to improve the software development lifecycle through Generative AI technologies
Lead developer onboarding, technical enablement, and adoption efforts while establishing best practices for prompt engineering, workflow integration, and AI-powered development
Design, implement, and operationalize solutions leveraging Agentic AI, multi-agent systems, autonomous workflows, MCP integrations, and AI orchestration patterns
Monitor platform adoption, utilization, performance, and business outcomes
Develop metrics, dashboards, and reporting frameworks for GenAI FinOps initiatives
Provide hands‑on troubleshooting, performance optimization, and technical guidance to engineering teams
Ensure solutions align with enterprise architecture, security, governance, compliance, and Responsible AI requirements
Contribute to InnerSource initiatives and reusable enterprise engineering capabilities
Collaborate with technical experts, senior technology teams, and external industry groups to resolve complex technical issues
Lead projects, teams, or serve as a peer mentor

Requirements

5+ years of Software Engineering experience or equivalent demonstrated through work experience, training, military experience, or education
5+ years of experience developing enterprise applications using Java, Python, or comparable technologies
1+ years of experience with AI-assisted/autonomous software engineering platforms such as GitHub Copilot, Devin, Claude Code, Cursor, or similar technologies
1+ years of experience building and deploying AI-powered applications using LLMs and Generative AI technologies
Experience designing and implementing distributed systems, APIs, microservices, and event‑driven architectures
Hands‑on experience with CI/CD pipelines, source control platforms, developer tooling, and software engineering best practices
Experience working with cloud‑native technologies and containerized platforms
Strong technical leadership, problem‑solving, and collaboration skills
Experience with enablement and training of AI platforms such as GitHub Copilot, Devin, Claude Code, Cursor, or similar technologies
Strong knowledge of Agentic AI, Retrieval‑Augmented Generation (RAG), Fine‑Tuning, prompt engineering, multi‑agent architectures, and MCP integrations
Experience developing scalable AI platforms and engineering enablement solutions
Experience with software engineering analytics, developer productivity measurement, and outcome‑based reporting
Knowledge of GenAI FinOps, technology cost management, and value realization frameworks
Experience working in highly regulated enterprise environments with governance, security, and compliance requirements
Not eligible for Visa sponsorship

Core Competencies

Demonstrates expertise in leading the design and development of AI‑assisted engineering solutions, with a strong focus on integrating Generative AI technologies into enterprise software development lifecycles. Proficient in technical leadership, collaboration, and the implementation of best practices for AI‑powered development and operationalization.

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