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About This Role
Software Engineer – AI-Enabled Vulnerability Research
An active TS//SCI clearance with polygraph is required for this role
Hey!
Bitwise is a leading provider of mission-focused intelligence solutions that advance national security for the Intelligence Community and Department of Defense. We're a small and growing company, so you can expect to hop in on the ground floor with us and be a consequential member of the team. You'll be more than a contract performer for us — you'll also be asked for ideas to improve our company and improve your career, and you'll contribute to our team culture. We value growth and community above almost all else, so we gather regularly for game nights, happy hours, tech talks, and plenty more. We think you'll like it here!
Remember, Bitwise is not a cult.
What We Look For
Bitwise hires talented engineers who are driven by purpose and who value a culture of technical excellence, growth, and overall wellness. We deliver new and innovative intelligence solutions to our customers at the very forefront of our country's national security missions. And we do it every single day. Our work matters, and so will you.
We ask that every new hire be able to:
- Contribute meaningful thought leadership — if not right away, over time
- Interact with our customers and earn their confidence in your abilities
- Be detailed, even if that means taking a little more time to get it right
- Contribute their ideas and ideals to improve all aspects of our company
- Allow us to invest in their education so we both grow together
- Know and live our core values every single day
About this Role
You will design, develop, and integrate AI-enabled capabilities that support computer network exploitation and vulnerability research. This role combines strong software engineering fundamentals with practical knowledge of vulnerability research, program analysis, and AI-assisted research workflows. You'll independently own complex features and subsystems, translate mission needs into technical designs, and deliver reliable software from prototype through deployment.
You will develop agentic AI harnesses that connect large language models, research tools, instrumented execution environments, and backend services to support repeatable, evidence-driven analysis. Working alongside vulnerability researchers, AI/ML engineers, and mission stakeholders, you'll make sound architectural decisions, evaluate AI-generated findings, and improve the quality and effectiveness of research workflows. This position also includes mentoring engineers and contributing to technical direction and engineering standards.
Your Responsibilities:
- Design, develop, and maintain AI-enabled software and research tooling supporting computer network exploitation and vulnerability research workflows
- Own the design and delivery of complex features and subsystems, including requirements refinement, implementation, testing, deployment, and sustainment
- Develop and integrate agentic AI harnesses that orchestrate research tools, manage execution state, collect evidence, and evaluate results
- Build and extend sandbox-based dynamic analysis capabilities for executing and observing software, capturing runtime behavior, and reproducing suspected vulnerabilities
- Integrate debugging, instrumentation, fuzzing, crash analysis, and related research tools into automated or researcher-directed workflows
- Establish repeatable evaluations that measure finding validity, reproducibility, false-positive rates, and the usefulness of AI-assisted analysis
- Develop backend services, APIs, data pipelines, and user interfaces that make research capabilities accessible and results traceable
- Troubleshoot complex issues across application code, AI integrations, research tooling, and execution environments; improve performance, reliability, and observability
- Lead design and code reviews within assigned areas, document technical decisions, mentor engineers, and communicate progress, risks, and tradeoffs to stakeholders
Requirements
- 12+ years of relevant experience with a B.S. in a technical discipline, or 16+ years of relevant experience without a degree
- Demonstrated experience independently designing, implementing, testing, and delivering complex software features or subsystems, with sound judgment about architecture, maintainability, and operational requirements
- Proficiency in Python and experience building maintainable, tested software using modular design and appropriate object-oriented programming practices
- Demonstrated expertise in AI-enabled computer network exploitation or vulnerability research, including integrating AI capabilities into research workflows and critically evaluating their outputs
- Experience with vulnerability research or software analysis techniques, such as reverse engineering, debugging, dynamic analysis, fuzzing, or crash triage
- Working knowledge of isolated execution environments and dynamic analysis concepts, including runtime instrumentation, execution tracing, environment reproducibility, and evidence collection
- Experience developing LLM applications or agentic systems that use external tools, structured outputs, workflow state, error handling, and evaluation
- Experience developing backend services and REST APIs using frameworks such as FastAPI, Flask, or Django, and working with relational databases such as PostgreSQL
- Experience working in Linux environments, with an understanding of operating system behavior, processes, memory, and networking relevant to software analysis
- Experience using Git, automated testing, CI/CD, and code review to deliver reliable software collaboratively
- Ability to translate ambiguous requirements into actionable technical work, explain technical tradeoffs, and provide effective guidance to other engineers
Preferred Skills
- Hands-on experience conducting dynamic vulnerability research in sandbox environments, including configuring instrumented targets, controlling execution, capturing runtime evidence, and reproducing findings across clean environment resets
- Experience building AI agents that interact with debuggers, fuzzers, emulators, or other analysis tools within controlled research environments
- Experience with virtualization, emulation, snapshots, and automated provisioning of repeatable analysis environments
- Experience with C/C++, assembly, binary analysis, memory corruption analysis, or operating system internals
- Experience designing evaluation datasets and benchmarks for AI-assisted vulnerability discovery, triage, or validation
- Experience with retrieval-augmented generation, vector databases, or search platforms such as Elasticsearch, Qdrant, or ChromaDB
- Experience building researcher-facing interfaces using TypeScript, React, or comparable technologies
- Contributions to vulnerability research, security tooling, open-source projects, or relevant technical publications
️ Benefits at Bitwise
- Top salaries because we're top performers
- Pick your PTO — Everyone values time and money differently, so we give you the flexibility to choose between 3 and 5 weeks of PTO with a corresponding adjustment to your pay. Your choice, your balance.
- All 11 federal holidays, paid!
- Up to 2 snow days, paid!
We'll quadruple (4x!) the first 6% you contribute to your 401(k), giving you up to a 24% company match. Contributing less than 6%? Unclaimed matches come right back to you as extra income, giving you a guaranteed 24% that goes to your retirement, to your paycheck, or both. C'mon now!
- 100% employer-paid medical, dental, vision, life, and disability insurances. That's a lot. Already covered on health insurance? No problem — we'll trade you this benefit for a boost to your salary instead.
- $5,250 annual education assistance for training, certifications, tuition, and even student loan repayments.
Spot bonuses for obtained certifications, customer recognition, and just about anything else that makes us go "Hot damn!". We hope to say that many times about you.
Salary Range
$282,000 – $332,000
This range includes our flex income and depends upon your annual work hours.
Salary is determined on an individual basis following the interview process and considering various factors such as years of experience, skills, education, and certifications.
️ What to Expect After Applying
You'll get an email from us right away to acknowledge your application. After that, we'll:
- Send over additional company materials for you to review
- Schedule a video call to talk about you, our company, and your place in it
- Craft a delightful offer package for you and record a video walkthrough
- Work closely with you through onboarding. We'll keep it joyful and easy.
ℹ️ Disclaimers
Bitwise is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other legally protected status. All employment decisions are based on qualifications, merit, and business needs.
Compensation for this position, including all compensation options, will be determined on an individual basis following the interview process.
If you require accommodations at any stage of the application or interview process, please reach out to us.
Last updated: 10/19/26
Salary Context
This $282K-$332K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $192K across 244 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 10,827 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Bitwise, LLC, 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 1,689 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($307K) sits 40% above the category median. Disclosed range: $282K to $332K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
Bitwise, LLC AI Hiring
Bitwise, LLC has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Columbia, MD, US. Compensation range: $233K - $332K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 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 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). 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 (122) are outnumbered by mid-level (5,256) and senior (3,922) 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 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 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 $213,480. Top-quartile roles start at $264,111, 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 $266,050 median, while Prompt Engineer roles sit at $140,000. 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 (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 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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