Candidates with experience in agentic systems and government AI deployment will find this remote-first, mission-critical role with a focus on real-world performance and security clearance requirements.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Striveworks via Greenhouse
“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks
The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.
Striveworks was built to solve that problem.
What you’ll build
Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.
As a Senior Machine Learning Engineer, Agentic Systems, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you’ll develop machine learning solutions, orchestrate complex data and agentic workflows, and help shape the capabilities of Chariot, our proprietary AI operations platform. You’ll work across models, agents, tools, and workflows to build reliable and effective AI systems while analyzing and improving their performance and usability. Your work will inform platform improvements, expand our capabilities, and extend to the field through mission-critical deployments, direct customer contact, and insights that shape what we build next.
What it’s like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we’re looking for
A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience
Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
Experience designing, building, evaluating, and optimizing LLM-powered agents and agentic workflows
Experience integrating AI systems with external tools, APIs, MCP servers, and enterprise data sources
Experience developing evaluation approaches and frameworks to measure agent performance, reliability, and safety
Familiarity with retrieval-augmented generation (RAG), tool use, planning, and multi-agent architectures
Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
Strong software engineering fundamentals, including algorithms, data structures, design patterns, proficiency in at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
US citizenship with eligibility and willingness to obtain and maintain a Secret US security clearance
The following isn’t required, but we’d love to see it:
An advanced degree in data science, machine learning, computer science, or a related discipline
Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], infrastructure as code, major cloud architectures)
Experience with a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, telemetry signals)
Experience defining, scoping, planning, and delivering complex technical solutions
Experience leading a small team
Experience delivering technology solutions in secure government environments
Active Secret (or above) US security clearance
This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 20% of the time.
Compensation
The anticipated base pay range for this position is $160,000–$200,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.
Benefits include:
Medical/dental/vision insurance
Voluntary life, long-term disability, accident, and hospital indemnity insurance
HSA and FSA (including dependent care FSA) plans
401(k) plan
Unlimited PTO
Paid parental leave
Ready to build systems that work for a mission that matters? Let’s talk.
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.
Source: Striveworks careers (Greenhouse)