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About This Role
At Two Six Technologies, we build, deploy, and implement innovative products that solve the world's most complex challenges today. Through unrivaled collaboration and unwavering trust, we push the boundaries of what's possible to empower our team and support our customers in building a safer global future.
About the Role
We are seeking an experienced Senior Platform Software Engineer (AI Specialist) to join our core Platform Team. Our platform functions as a curated, self-service product designed to accelerate delivery and reduce cognitive load for our Stream-Aligned feature teams.
In this role, you will be the primary architect and technical owner of our internal AI orchestration ecosystem. You will not build isolated features; instead, you will design, deploy, and maintain the underlying infrastructure, developer tools, and shared services that enable full-stack feature developers to seamlessly integrate agentic AI capability into their codebases.
This is a full-time, hybrid position that requires work at our Arlington office three days per week. Applicants must be U.S. citizens and have the ability to obtain and maintain up to a Top Secret/SCI security clearance.
What You Will Do
- Own AI Infrastructure & Orchestration: Establish, scale, and maintain a robust internal orchestrator layer to manage LLM interactions, tool execution loops, context windows, and token allocation efficiently.
- Build Self-Service Tools & Libraries: Design and package shared utilities, client libraries, and standardized abstractions (such as managed agentic skills and database migration patterns) so feature teams can independently leverage AI tools.
- Optimize for Fast Flow: Partner with Stream-Aligned developers to evaluate, select, and optimize prompt engineering guardrails, embedding stores, and testing patterns, ensuring automated pipelines protect flow and speed up deployment frequency.
- Drive Platform Architecture: Ensure platform components are hosted independently, version-controlled, and seamlessly importable, allowing for safe rollbacks and clean operational boundaries within a monorepo structure.
- Collaborate and Upskill: Participate in internal guilds and cross-team workshops, acting as a technical consultant to ensure architectural decisions across the UI, API, and data model layers remain fluid and stable.
What We Are Looking For
- AI Orchestration Focus: Proven engineering experience building and deploying AI agent frameworks, orchestrators, or middleware. Strong familiarity with agentic orchestration frameworks such as LangGraph/LangChain and/or PydanticAI, along with proficiency in advanced prompt management, token optimization, and managing external skill libraries.
- Full-Stack Application Engineering: Comfortable working across multiple layers of a modern web application stack—including frontend components, API service layers, and relational databases—to ensure friction-free platform adoption.
- Infrastructure as Code & Automation: Proficient with automated delivery tooling, container orchestration, and packaging systems to build "secure by default" execution environments.
- Agile Experience: Proven experience operating effectively within an Agile software development environment, paired with a strong understanding of continuous delivery metrics (such as Lead Time and Deployment Frequency) and a commitment to creating predictable automated testing guardrails over relying on gatekeeping steps.
- Autonomous & Collaborative: Comfortable taking ownership of technical initiatives, prioritizing work independently, and communicating proactively across team boundaries without requiring micromanagement.
- Clearance: Must be US Citizens and have the eligibility to obtain and maintain up to Top Secret/SCI security clearance.
Why This Role is Unique
You will not be stuck building isolated features or manual workarounds. You will have full organizational support to shift architectural foundations left, building a reliable infrastructure ecosystem that transforms our developer experience into a high-trust, fast-flowing environment.
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Two Six Technologies is an Equal Opportunity Employer and does not discriminate in employment opportunities or practices based on race (including traits historically associated with race, such as hair texture, hair type and protective hair styles (e.g., braids, twists, locs and twists)), color, religion, national origin, sex (including pregnancy, childbirth or related medical conditions and lactation), sexual orientation, gender identity or expression, age (40 and over), marital status, disability, genetic information, and protected veteran status or any other characteristic protected by applicable federal, state, or local law. For more information review the Two Six Technologies Equal Employment Opportunity and Affirmative Action Policy and the EEO Poster.
If you are an individual with a disability and would like to request reasonable workplace accommodation for any part of our employment process, please send an email to [email protected]. Information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations.
Additionally, please be advised that this business uses E-Verify in its hiring practices.
By submitting the following application, I hereby certify that to the best of my knowledge, the information provided is true and accurate.
Salary Context
This $140K-$200K range is below the median for AI Software Engineer roles in our dataset (median: $192K across 146 roles with salary data).
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 8,943 AI roles we're tracking, AI Software Engineer positions make up 4% of the market. At Two Six Technologies, 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 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($170K) sits 23% below the category median. Disclosed range: $140K to $200K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Two Six Technologies AI Hiring
Two Six Technologies has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Arlington, VA, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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