Applied AI Engineer 1
Posted 4 days ago
The role in short
Embed with intelligence operators to build and test agentic AI solutions, MCP servers, and data tools in Python.
Applied AI Engineer 1 - (Python, LLM, MCP)
Clearance: TS/SCI - Polygraph required
Position ID: 20-16-065-SWE1
Location: Columbia, Maryland
Description:
Brings AI into the operations organization, embedding engineers with the operators, analysts, and developers who carry out the CNO mission. Our engineers learn how those teams work, find the tasks that consume their time, and build AI agents and tools that let them move faster without giving up accuracy or control. We build on both frontier models and on-premises open-weight models, served through the customer's enterprise AI platform, and turn them into mission capabilities such as agents that triage incoming data, automate repetitive tradecraft, or research across disparate sources on an analyst's behalf. We are now introducing autonomous agents the mission can trust: agents that take real actions within guardrails, are measured against evaluations built with the people who use them, and log every step so a reviewer can follow what they did. As an Applied AI Engineer, you will join a forward-deployed team that works directly with a mission customer, building and improving the agents, Skills, and tools they use every day. You will work under the guidance of senior engineers, learn CNO tradecraft from the operators and analysts you support, and see the results of your work firsthand. This role suits an engineer with a solid software foundation who wants to grow quickly in applied AI.
- Develop and test components of agentic AI solutions in Python, including MCP servers, Skills, and integrations with mission data sources and tools.
- Participate in requirements discussions with operators and analysts, and learn their workflows and tradecraft.
- Build scripts and tools that convert, normalize, and extract information from customer data.
- Write test cases and evaluation examples that check whether AI capabilities return correct and reliable results.
- Use AI coding agents in daily development, and understand and review generated code before committing it.
- Collaborate with other engineers to test workflows, identify issues, and recommend fixes.
- Create documentation and user guides that help mission users adopt new AI tools.
Position Required Skills:
- Proficiency in Python, including working with JSON, REST APIs, and data manipulation.
- Understanding of software engineering fundamentals, including version control (Git), testing, and debugging.
- Familiarity with LLM concepts such as prompt engineering, structured outputs, and tool/function calling.
- Experience using AI coding assistants (e.g., Claude Code, Copilot) to write, debug, or test code.
- Familiarity with Linux environments and the command line.
- Strong communication skills and willingness to learn from senior engineers and mission subject matter experts.
Nice to Haves
- Experience building agentic workflows, MCP servers, or Skills.
- Experience with Docker, Kubernetes, or GitLab CI/CD.
- Experience with retrieval systems (RAG, vector databases, Elasticsearch).
- Experience building web interfaces with React or TypeScript.
- Background in cybersecurity, or knowledge of CNO operations and SIGINT collection and analysis systems.
SWE1 Qualifications:
A minimum of three (3) years of experience as a SWE, in programs and contracts of similar scope, type, and complexity is required. Bachelor's degree in Computer Science or related discipline from an accredited college or university is required. Four (4) years of additional SWE experience on projects with similar software processes may be substituted for a bachelor's degree.
Salary Range: $169k-$207k (Annually)
The range displayed above is a likely salary range for this position. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possible contractual requirements and could fall outside of this range.
Akina is a Woman Owned, Service Disabled, Veteran Owned, Small Business, looking for talented and ambitious individuals to join our team. We offer a generous compensation package that includes 24 days PTO accrued annually and 11 federal holidays. Our 401k is 100% vested on your start date and the company makes a direct contribution worth 10% of your salary. Akina covers 100% of healthcare costs for employees and 50% toward dependents. We offer educational assistance towards college classes and will cover costs associated with job related training and certifications.
Akina is committed to excellence and creating innovative and flexible solutions for our clients. We are a small company with an open ear to our employees' needs in order to attract and retain quality talent that enables our customer's mission.
We are an equal employment opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Prep for this interview
4 questions likely to come up at Akina, Inc., each matched to a line in this posting.
- 1LLMs, RAG and agents
They wrote: “Familiarity with LLM concepts such as prompt engineering, structured outputs, and tool/function calling.”
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.
- 2Cloud, deployment and security
They wrote: “Experience with Docker, Kubernetes, or GitLab CI/CD.”
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.
- 3Integrations and APIs
They wrote: “Develop and test components of agentic AI solutions in Python, including MCP servers, Skills, and integrations with mission data sources and tools.”
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.
- 4Coding
They wrote: “Proficiency in Python, including working with JSON, REST APIs, and data manipulation.”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
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