Senior GenAI Engineering Lead — Planning & Execution (Python)

Evolver

Iowa

On-site

USD 180,000 - 260,000

Full time

11 days ago

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Job summary

Evolver, a US-based AI company, is seeking a Senior GenAI Engineering Lead to own the planning and execution layer of our AI platform. You will lead a small team of developers, translate business goals into a prioritized platform roadmap, and drive delivery from design through production.

In this hands-on role, you will contribute substantial Python engineering work, shape architecture for scalable planner and executor components, and collaborate with product, domain experts, and security teams

Qualifications

  • 8+ years of professional software engineering experience with advanced Python proficiency.
  • Experience owning a technical roadmap and/or leading a small development team to deliver software.
  • Hands-on experience building production-level AI-powered workflows or agent systems.

Responsibilities

  • Own the roadmap and delivery: define priorities for the planning and execution layer and align milestones with customer needs and business goals.
  • Evolve the planner and executor architecture, define boundaries, interfaces, and state management for scalability and reliability.
  • Advance planning and orchestration: develop goal decomposition, agent/tool selection, dependency management, and adaptive replanning.
  • Deliver reliable, observable execution: build resilient workflows with persistent state, failure recovery, and human oversight; establish monitoring to improve quality and cost.
  • Lead a small development team: set technical direction, coordinate work, coach developers, and write/review production Python code with cross-team collaboration.

Skills

Python
API design
Asynchronous programming
Testing
Production debugging
LLM-based planning
Agent orchestration
Cloud-native services
Databases
Queues

Education

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

Tools

Docker
Kubernetes
Cloud-native services
Databases
Message queues

Job description

Senior GenAI Engineering Lead — Planning & Execution (Python)

About Us

We are an innovative AI company with a team of 100+ people focused on transforming core enterprise functions in Fortune 500 companies. Our platform combines a rich understanding of a company’s current state with deep domain expertise to execute these functions with accuracy and consistency through code, statistical methods, and guided ML and LLM execution. It handles processes end-to-end, engaging humans when needed to maximize efficiency and quality.
Join us at the forefront of AI innovation, where your expertise will directly shape the future of enterprise operations.

Role Overview

We are looking for a hands‑on engineering lead tolead a small team of developers andown the roadmap, architecture, and delivery of the planning and execution layer of our AI platform.

This layer translates user goals into actionable plans and coordinates agents, tools, data, and human input to carry those plans through to completion. You will define how workflows are planned, executed, monitored, and adapted as new information becomes available.

Working closely with product leaders, domain experts, and engineering teams, you will turn business needs into a prioritized platform roadmap and guide your team in delivering it. This role combines team leadership, including setting direction, coordinating work, and coaching developers, with substantial hands‑on Python development from early design through production operation.

Key Responsibilities

  • Own the roadmap and delivery:Define priorities for the platform’s planning and execution layer, translate them into milestones, and lead delivery aligned with customer needs and business goals.
  • Evolve the platform architecture:Lead the evolution of the planner and executor architecture, defining component boundaries, interfaces, and state management to support scalability, extensibility, and reliability.
  • Advance planning and orchestration:Develop capabilities for goal decomposition, agent and tool selection, dependency management, and adaptive replanning based on execution feedback.
  • Deliver reliable, observable execution:Build resilient workflows with persistent state, failure recovery, and human oversight. Establish evaluations and monitoring to improve quality, latency, and cost.
  • Lead a small development team:Set technical direction, coordinate work, coach developers, and maintain engineering quality while writing and reviewing production Python code. Collaborate with product, domain, infrastructure, and security teams to deliver enterprise-ready capabilities.

Qualifications:

Experience:

  • 8+ years of professional software engineering experience, with advanced proficiency in Python.
  • Experience owning a technical roadmap and/or leading a small development team to deliver software.
  • Hands‑on experience building production‑level AI‑powered workflows or agent systems

Education:

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

Technical Skills:

  • Strong Python engineering skills, including API design, asynchronous programming, testing, and production debugging.
  • Experience with LLM‑based planning, tool calling, structured outputs, context management, and agent orchestration.
  • Ability to design execution systems that handle partial failures, retries, concurrency, and persistent state.
  • Experience evaluating AI behavior and using traces, metrics, and logs to improve system performance.
  • Familiarity with retrieval‑augmented generation and integrating structured and unstructured data into agent workflows.
  • Experience with cloud‑native services, databases, queues, and deployment practices.

Soft Skills:

  • Ability to turn ambiguous requirements into a clear roadmap and achievable delivery milestones.
  • Strong architectural judgment and the ability to communicate technical tradeoffs.
  • Experience collaborating with product managers, domain experts, and engineering teams.
  • A practical approach to balancing experimentation with production reliability.
  • Comfort taking ownership in a fast‑moving startup environment.
  • Competitive Compensation:Tailored to your experience and skill set.
  • Career Growth:Opportunities to expand your technical and leadership responsibilities.
  • Meaningful Impact:Direct ownership of core platform capabilities that shape how AI delivers professional services.
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