Senior DevOps & AI Engineer

About Innovas
At Innovas, we are transforming the way government innovates by delivering the mechanisms that turn ideas into action. We bring together the right people, processes, and technologies to accelerate progress where it matters most.
With a focus on impact over bureaucracy, collaboration over silos, and solutions over status quo, we we're built to act. Our team is made up of passionate problem-solvers, innovators, and experts who thrive on tackling meaningful challenges and delivering results. At Innovas, every role contributes to something bigger. Whether you’re supporting technology acquisition, improving processes, or enabling collaboration across organizations, your work helps move critical missions forward.
Join Innovas and help shape the future of government innovation.
Why Work At Innovas
Work on problems that matter.
At Innovas, your work directly supports innovation that shapes our nation’s future and delivers solutions with real-world impact.
Be part of something built differently.
Our teams are empowered to focus on solving problems, creating value, and exceeding expectations.
Bring ideas to life.
Work alongside passionate problem-solvers who thrive on tackling complex challenges and turning possibilities into progress.
Grow alongside a team of experts.
Our people bring diverse experiences from government, military, industry, technology, and entrepreneurship.
Job Description
Reporting to the Senior Director of Engineering & Architecture, this senior individual contributor turns engineering priorities into working tools and automated workflows that help the team deliver customer-facing products. The role focuses approximately 40% on development infrastructure and DevOps, 40% on AI agents and orchestration, 10% on integrations and reporting, and 10% on stakeholder engagement and Scrum facilitation. The initial priorities are to establish the new DevOps environment and implement multi-agent workflows that execute approved backlog items and submit code through pull requests for human review. The role requires deep experience in automation, the software development lifecycle, CI/CD, and AI agent orchestration. Responsibilities include selecting and customizing established tools where practical, deploying cloud and local inference capabilities, and partnering with engineers and business stakeholders to improve delivery. Substantial application development experience is preferred; the core requirement is demonstrated ability to build and operate effective engineering automation.
Essential Duties And Responsibilities
Development Infrastructure and DevOps
Design and implement the development and DevOps platform from scratch, initially using Azure DevOps Server, within the architecture and priorities established with the Senior Director.
Own source control, repository standards, build runners, artifact and package repositories, development tooling, and the integrations connecting the engineering toolchain.
Build CI/CD pipelines covering automated testing, quality and security checks, versioned artifacts, deployment approvals, release automation, and rollback.
Provision repeatable development, test, staging, and production environments using infrastructure as code and configuration automation across cloud, on-premises, and hybrid deployments.
Support Windows, Linux, and containerized workloads; automate engineer onboarding and environment setup, and coordinate platform access, workload identities, and secrets with IT Services.
Document platform architecture, operating procedures, and recovery steps; improve reliability and remove recurring manual work and delivery bottlenecks.
AI Agents and Workflow Orchestration
Evaluate, select, integrate, and customize established AI agent tools and orchestration frameworks. Develop extensions and connectors where needed to support Innovas workflows.
Implement workflows that read from a curated, prioritized backlog, gather requirements and repository context, decompose work, assign tasks to agents, coordinate dependencies, and track execution.
Configure and develop agents for software development, testing, documentation, infrastructure automation, integrations, and approved business process automation.
Connect agents to development tools, approved data sources, and execution environments; manage task state, isolated workspaces, retries, failure handling, and traceability to backlog items.
Ensure agent-produced code is submitted through pull requests for human review, with appropriate test results and supporting context. Maintain traceability from the backlog item to the proposed change.
Develop and implement access controls, execution boundaries, human approval gates, and accountability for agent actions in concert with the Senior Director and CTO.
Evaluate agent quality and task completion against acceptance criteria; refine workflows using engineer feedback, failed runs, rework, and the cost of accepted results.
AI Inference Infrastructure
Deploy and operate cloud and local model inference services, model gateways, and the software supporting agent execution across hybrid environments.
Benchmark and tune inference latency, throughput, concurrency, memory consumption, and operating cost against the needs of developers and agents.
Manage model configuration, versioning, routing, provider integrations, and controlled upgrades; validate model suitability for the tasks and contexts it will support.
Partner with IT Services on local inference hardware, hosting, capacity, and infrastructure maintenance, retaining engineering ownership of inference software and agent integrations.
Products and Custom Integrations
Support the delivery of customer-facing products through engineering automation, agent workflows, deployment tooling, and custom integrations.
Build API connectors and integration workflows between products and internal business systems, including finance systems where product requirements call for them.
Develop custom integrations for internal systems where applicable, in partnership with business owners and IT Services. Document data flows, failure handling, and support responsibilities.
Production Support and Operational Ownership
Own the engineering software and automation supporting development, releases, custom applications, custom integrations, and inference services. IT Services owns infrastructure patching, routine monitoring, and SaaS application administration.
Provide application and agent telemetry, diagnostic information, alerts, and runbooks that support IT monitoring and escalation. Investigate and resolve failures requiring changes to engineering-owned software or configuration.
Support production releases, rollback, and application recovery; participate in incident reviews and implement lasting fixes in coordination with engineers and IT Services.
Provide initial on-call support for engineering-owned services. Prepare documentation, escalation procedures, and knowledge transfer for site reliability engineering (SRE) staff as coverage is established.
Stakeholder Partnership and Scrum Facilitation
Work directly with business stakeholders to understand product needs, clarify requirements, identify opportunities for automation, and demonstrate delivered capabilities.
Partner with the Senior Director and business stakeholders to curate and prioritize the backlog; document work items, dependencies, and acceptance criteria suitable for both engineers and AI agents.
Coordinate requirements approval by the Senior Director or CTO in partnership with the business and organize user acceptance testing and feedback on delivered work.
Serve as Scrum Master, facilitating planning, daily standups, reviews, and retrospectives. Track impediments and dependencies, coordinate their resolution, and communicate progress and delivery risks.
Help the team improve its delivery practices through practical process changes, useful automation, and clear documentation; support adoption of the new engineering tools and workflows.
Reporting and Performance Measurement
Build reports, KPIs, and dashboards showing operational health, engineering delivery, team performance, and AI agent performance.
Establish baselines and agreed targets with the Senior Director. Track pipeline reliability, deployment frequency, lead time, failed changes, recovery, and environment readiness.
Measure agent task completion, human acceptance, rework, failures, execution time, and cost per accepted result; connect these measures to product outcomes and software quality.
Provide visibility into inference performance, utilization, capacity, and spending. Explain trends and recommend concrete improvements to engineering leadership and stakeholders.
Required Qualifications
10+ years of experience automating infrastructure, technology operations, development workflows, or business processes, with substantial practical experience in DevOps and engineering automation.
Demonstrated ability to build development infrastructure and delivery platforms, including source control, build systems, artifact repositori

Skills
Linux, Azure, CI/CD, Automation Testing, Scrum, Onboarding, Documentation

Experience
10+ yrs

Work arrangement
Yes