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About This Role
Themis Insight solves difficult business, IT, and analytic problems by addressing the whole problem – not just the symptoms – using interdisciplinary approaches that are both practical and innovative. We provide fresh alternatives to ordinary, mainstream consulting firms through small, highly skilled, and hand-picked teams that can meet clients' needs in any industry. Our broad interdisciplinary understanding allows us to provide the right solution, even if it is from outside the industry or traditionally defined problem space. We bring Public and Private, Civilian and Military expertise to every case.
We are hiring a Software Engineer (AI Automation, Python, CI/CD, AWS) to work in the Ft. Meade, MD vicinity. Position location is subject to change based on central MD client's needs.
Required: TS/SCI with a Polygraph
Expected tasks include:
- AI workflow automation scripts
- Dev/test pipeline construction
- System integration
- Performance optimization for 1M+ requests/day
- Monitoring implementation
Description:
The Software Engineer develops, maintains, and enhances complex and diverse software systems (e.g., processing-intensive analytics, novel algorithm development, manipulation of extremely large data sets, real-time systems, and business management information systems) based upon documented requirements. Works individually or as part of a team. Reviews and tests software components for adherence to the design requirements and documents test results. Resolves software problem reports. Utilizes software development and software design
methodologies appropriate to the development environment. Provides specific input to the software components of system design to include hardware/software trade-offs, software reuse, use of Commercial Off-the-shelf (COTS)/Government Off-the-shelf (GOTS) in place of new development, and requirements analysis and synthesis from system level to individual software components.
The Software Engineer shall possess the following capabilities:
- Analyze user requirements to derive software design and performance requirements
- Debug existing software and correct defects
- Provide recommendations for improving documentation and software development process standards
- Design and code new software or modify existing software to add new features
- Integrate existing software into new or modified systems or operating environments
- Develop simple data queries for existing or proposed databases or data repositories
- Applies knowledge of ITOM, ITSM, HRSD, CSM and/or Service Portal.
- Codes with programming languages and databases including HTML, CSS, JavaScript.
- Write or review software and system documentation
- Serve as team lead at the level appropriate to the software development process being used on any particular project
- Design or implement complex database or data repository interfaces/queries
- Develop or implement algorithms to meet or exceed system performance and functional standards
- Assist with developing and executing test procedures for software components
- Develop software solutions by analyzing system performance standards, confer with users or system engineers; analyze systems flow, data usage and work processes; and investigate problem areas
- Modify existing software to correct errors, to adapt to new hardware, or to improve its performance
- Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design
- Design or implement complex algorithms requiring adherence to strict timing, system resource, or interface constraints; Perform quality control on team products
- Implement recommendations for improving documentation and software development process standards
- Oversee one or more software development teams and ensure the work is completed in accordance with the constraints of the software development process being used on any particular project
- Confer with system engineers and hardware engineers to derive software requirements and to obtain information on project limitations and capabilities, performance requirements and interfaces
- Coordinate software system installation and monitor equipment functioning to ensure operational specifications are met
Individual Capabilities/Experience 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.
- Two (2) or more years experience developing and customizing core applications such as Incident, Problem, Change, Knowledge, and Service Catalog
- Four (4) or more years of IT application systems experience in technology solutions delivery is required.
Individual Capabilities/Experience Desired:
- Python/Scripting
- CI/CD
- Jenkins/GitLab/Code Pipeline
- AWS
- API Integration
- Algorithm development
Themis Insight has all the PERKS!
You are our most valuable resource — your ambition, your knowledge, your creativity. We offer an industry-leading set of benefits to supplement your normal salary compensation. Themis Insight has you covered with flexible ways to balance work and home life, full health benefit premium coverage, and generous contributions toward your retirement.
- Competitive health, dental, and vision plans with 100% paid premiums.
- 401k: We contribute 6% even if you don't!
- Time Off: 11 standard holidays, and 25 days of PTO
- Career Development: Get career counseling and individualized career development plans, including education and training.
- Employee referral bonuses for successful hires
Themis Insight is an Equal Opportunity/Affirmative Action employer.
Themis Insight provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Themis Insight, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Themis Insight AI Hiring
Themis Insight has 2 open AI roles right now. They're hiring across AI Software Engineer. Positions span Fort Meade, MD, US, Columbia, MD, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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