Forward Deployed AI Engineer
Posted yesterday
The role in short
Build and deploy internal AI agents and applications for MISO's business teams, focusing on production readiness, governance, and knowledge transfer to internal engineers.
The Forward-Deployed AI Engineer will transform MISO’s most important business challenges into practical, production-ready AI solutions. Working side‑by‑side with domain experts, this role blends data, AI, and software engineering to rapidly design, build, and deploy intelligent applications and agents. You will own the full lifecycle from problem discovery through production adoption, ensuring each solution delivers clear and measurable business value. By developing secure, reliable, and reusable AI components within MISO’s enterprise standards, this role accelerates innovation and reduces reliance on external vendors. Success in the first year is demonstrated by faster delivery of priority AI use cases, measurable improvements in decision quality and operational efficiency, and solutions that meet defined performance and governance criteria in production. Ultimately, the engineer empowers internal teams to independently operate and extend these solutions while contributing reusable patterns and assets that strengthen MISO’s broader AI ecosystem.
Some of the impactful contributions you’ll make as MISO’s Forward-Deployed AI Engineer include:
- Partnering directly with the business to understand real workflows, uncover operational challenges, and translate domain expertise into clear technical requirements and actionable solution designs.
- Leading AI and agentic solution delivery end‑to‑end - from discovery and architecture through data integration, testing, deployment, observability, and continuous improvement.
- Rapidly producing working increments using governed production or representative data, demonstrating visible progress to domain experts on a frequent, iterative cadence.
- Designing and implementing AI applications, copilots, agents, retrieval pipelines, APIs, and automation that integrate seamlessly with MISO’s enterprise technology environment and standards.
- Establishing robust evaluation methods and safety measures that validate accuracy, reliability, hallucination risk, workflow completion, and business usefulness against defined thresholds.
- Building solutions using composable architectures, reusable services, and model‑agnostic patterns that reduce lock‑in and enable scaling across the enterprise.
- Ensuring long‑term sustainability by creating runbooks, documentation, and reusable assets, and by pairing with internal engineers to transfer knowledge and ensure independent operation.
- Delivering measurable business outcomes (including faster delivery from discovery to production, improved decision) making and efficiency, and AI solutions that teams can operate and extend without ongoing reliance on the Forward‑Deployed AI Engineer.
You’ll need the following skills to be successful as our Forward-Deployed AI Engineer:
- Strong foundational education in computer science, engineering, data science, or a related technical field, with an advanced degree preferred.
- Extensive experience (15+ years) across software, data, AI/ML engineering, solution architecture, or product engineering, including hands‑on delivery of production AI/ML solutions.
- Deep proficiency in modern programming languages—especially Python—and strong SQL skills, with the ability to design secure, scalable back‑end services and APIs.
- Expertise integrating applications with enterprise data sources, APIs, cloud services, and distributed systems, ideally within a Microsoft Azure environment.
- Demonstrated experience with cloud‑native engineering practices, CI/CD, automated testing, observability, production support, and containerization technologies.
- Strong applied knowledge of generative AI, agent orchestration, retrieval‑augmented generation, prompt/context engineering, and AI evaluation frameworks.
- Ability to translate complex business workflows into robust technical solutions by working directly with domain experts and converting operational needs into actionable requirements.
- Familiarity with AI observability, governance, human‑in‑the‑loop workflows, and model reliability practices to ensure safe and effective production AI operations.
Appropriate level will be determined based upon experience and knowledge.
Transformative innovation is happening in the electric industry, from digitalizing homes and distributed resources to renewable energy and an ever-changing grid. MISO manages the electricity superhighway in the Central U.S. and through use of groundbreaking research and advanced technology, our highly skilled employees ensure power flows reliably to 45 million Americans. Operating the electricity grid, running a robust energy market, planning for a bright future – it’s what our immensely hardworking and dedicated team does every day.
The base salary compensation range being offered for this role is $190,000 - $215,000 USD annually. Base salary range for this position is included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, and qualifications/experience.
Position is also eligible for an annual bonus if individual performance and company objectives are met. At MISO we offer a comprehensive benefits package, including 401k, vacation, sick and safe time, available on your first day of employment.
#DiscoverMISO #MISOCareers #lifeatMISO #weareMISO
#LI-ONSITE
#LI-JH1
Qualifications
Skills
Behaviors
:
Motivations
:
Education
Preferred
Bachelors or better in Computer Science or related field.
Bachelors or better in Data Science or related field.
Bachelors or better in Engineering or related field.
Experience
Preferred
15 years:
Extensive experience across software, data, AI/ML engineering, solution architecture, or product engineering, including hands on delivery of production AI/ML solutions.
Licenses & Certifications
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.
Prep for this interview
5 questions likely to come up at MISO, each matched to a line in this posting.
- 1Discovery and scoping
They wrote: “Partnering directly with the business to understand real workflows, uncover operational challenges, and translate domain expertise into clear technical requirements and actionable solution designs.”
A customer says “we want AI in our claims process.” What do you ask in the first meeting?
How to answer
Why they ask: Most FDE work starts this vague. They want to hear you find the real problem before you pick a tool.
- Map the current process: who touches a claim, in what order, with which systems
- Find the slowest or most error-prone step and ask what it costs them
- Agree on one measurable goal (for example time per claim, or error rate)
- Ask what data you can access, and who signs off on security
Tip: Ask about the work, not the technology. Who does it today, how long it takes, what a mistake costs, and how they'd know it got better.
- 2Integrations and APIs
They wrote: “Leading AI and agentic solution delivery end‑to‑end - from discovery and architecture through data integration, testing, deployment, observability, and continuous improvement.”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 3Data and SQL
They wrote: “Deep proficiency in modern programming languages—especially Python—and strong SQL skills, with the ability to design secure, scalable back‑end services and APIs.”
Write a query that finds each customer's first and most recent order.
How to answer
Why they ask: A quick check that you're comfortable with grouping, joins and window functions.
- Clarify the tables and what counts as an order (cancelled ones?)
- Use MIN/MAX with GROUP BY, or ROW_NUMBER() if you need the whole row
- Handle ties on the same timestamp, and customers with no orders
- Explain how you'd test it on a few known customers
Tip: Say what you'd check in the data before writing the query: duplicates, time zones, nulls.
- 4LLMs, RAG and agents
They wrote: “Strong applied knowledge of generative AI, agent orchestration, retrieval‑augmented generation, prompt/context engineering, and AI evaluation frameworks.”
A customer wants a chatbot over their internal documents. How do you build it?
How to answer
Why they ask: RAG is the most common first project. They want the whole path, from messy files to answers people trust.
- Collect and clean the documents; handle permissions per user
- Split them into chunks, embed, and store with source links
- Retrieve, then answer with citations; say “I don't know” when retrieval is weak
- Build a test set of real questions with expected answers before launch
Tip: Spend more time on the data and on testing than on the model.
- 5Cloud, deployment and security
They wrote: “Expertise integrating applications with enterprise data sources, APIs, cloud services, and distributed systems, ideally within a Microsoft Azure environment.”
How would you debug a deployment that works in staging but fails at the customer's site?
How to answer
Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.
- Compare versions, config and environment variables
- Check network rules, proxies and certificates (common in enterprise)
- Look at resource limits and permissions
- Add the missing check to your install steps afterwards
Tip: List the usual suspects and how you'd check each without full access.
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