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About This Role
Job Family:
Software Development \& Support Travel Required:
None Clearance Required:
Ability to Obtain Public TrustWhat You Will Do
Guidehouse Technology is seeking a highly skilled and motivated AI\-focused Software Engineer to join our dynamic team. In this role, you will work with federal clients to design, develop, and deploy innovative Artificial Intelligence and Machine Learning solutions that address immediate mission challenges. You will be a key contributor on a team of data scientists, developers, and subject matter experts, applying best practices to build robust AI applications, sophisticated data pipelines, and intelligent systems.
The ideal candidate is a fast learner and rapid developer with a strong foundation in software engineering and demonstrable experience building production\-ready AI solutions from concept to deployment. The ideal candidate should also possess strong hands\-on expertise in Python, machine learning, graph analytics, natural language processing, and entity resolution. This combination of skills is essential for uncovering hidden patterns across large, disparate datasets in support of fraud detection, trafficking detection, and other mission\-critical investigative use cases.
A critical competency for this role is network analysis—the ability to link individuals, transactions, organizations, events, documents, and locations to identify relationships, detect anomalies, and expose organized illegal activities. In tandem, the candidate should be proficient in developing and applying AI/ML models for risk scoring, anomaly detection, pattern recognition, and investigative prioritization, enabling federal clients to enhance operational effectiveness and focus resources on the highest\-risk cases.
What You Will Do
- Design, develop, and deploy end\-to\-end AI/ML applications, with a focus on Retrieval\-Augmented Generation systems, AI chatbots, and agentic workflows.
- Construct and maintain scalable data pipelines for processing, transforming, linking, and feeding structured and unstructured data into AI models and applications.
- Develop machine learning models for risk scoring, anomaly detection, classification, clustering, and predictive analytics to support investigative and operational decision\-making.
- Apply graph analytics and network analysis techniques to identify hidden relationships among individuals, transactions, locations, organizations, and events.
- Implement entity resolution capabilities to match, deduplicate, and link records across large, disparate datasets.
- Apply NLP techniques to extract entities, relationships, topics, events, and indicators from unstructured text, documents, case notes, and other mission\-relevant data sources.
- Collaborate with cross\-functional teams to rapidly prototype and iterate on solutions for mission\-critical challenges in areas such as fraud detection, trafficking detection, data triage, search and optimization, and automated discovery.
- Develop and maintain REST APIs to serve model inferences and integrate AI capabilities into larger systems.
- Contribute to the team's software architecture design, ensuring solutions are scalable, reliable, secure, and efficient.
- Deploy and manage applications and models in cloud environments, primarily AWS, leveraging infrastructure\-as\-code and DevOps best practices.
What You Will Need
- Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
- Bachelor’s degree is required.
- Minimum SIX (6\) years of hands\-on experience with Python and JavaScript and/or TypeScript. A Master’s degree OR Industry Certification may be substituted for up to two years of relevant professional experience.
- Strong hands\-on experience with Python for AI/ML application development, data engineering, data analysis, and model implementation.
- Proven experience developing RAG applications, including implementing re\-ranking strategies.
- Experience building AI chatbots or conversational agents.
- Hands\-on experience with AI application frameworks such as LangChain, Haystack, crewAI, or similar.
- Strong knowledge of core Python data science and ML libraries, including NumPy, Pandas, Scikit\-learn, NLTK, and OpenCV.
- Demonstrated experience developing and applying machine learning models for classification, clustering, risk scoring, anomaly detection, and pattern recognition.
- Experience with graph analytics, network analysis, and relationship discovery across complex datasets.
- Experience with entity resolution, record linkage, deduplication, identity matching, or similar data matching techniques.
- Experience applying NLP techniques such as named entity recognition, text classification, semantic search, information extraction, topic modeling, and relationship extraction.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
- Experience with search technologies such as Elasticsearch or OpenSearch.
- Experience with relational databases, such as PostgreSQL or Oracle DB, and in\-memory analytics databases, such as DuckDB.
- Strong knowledge of SQL and data modeling techniques.
- Experience with cloud SDKs, such as Boto3 for AWS.
- Ability to work with large, disparate datasets and uncover hidden patterns, relationships, anomalies, and risk indicators.
- Strong analytical, problem\-solving, and communication skills, with the ability to translate mission needs into practical AI/ML solutions.
What Would Be Nice To Have
- Familiarity with agentic AI frameworks such as AWS Strands Agents, PydanticAI, or similar.
- Advanced prompt engineering skills for complex tasks beyond code generation.
- Experience with asynchronous Python development.
- Experience with MCP servers and tool calling within agentic workflows.
- Knowledge of GPU\-accelerated computing, CUDA, and hardware optimization for running ML models efficiently.
- Experience with graph databases or graph processing frameworks such as Neo4j, Amazon Neptune, TigerGraph, NetworkX, GraphFrames, or similar.
- Experience supporting fraud detection, trafficking detection, investigations, intelligence analysis, case management, or law enforcement\-adjacent mission environments.
- Experience building explainable AI/ML models that support analyst review, investigative workflows, and auditability.
- Experience integrating AI/ML capabilities into federal cloud environments while following security, privacy, and compliance best practices.
- Familiarity with geospatial analytics, temporal analytics, link analysis, or behavioral pattern detection.
- Experience designing AI/ML solutions that support human\-in\-the\-loop review, case prioritization, and investigative decision support.
The annual salary range for this position is $113,000\.00\-$188,000\.00\. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. What We Offer:
Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.
Benefits include:
- Medical, Rx, Dental \& Vision Insurance
- Personal and Family Sick Time \& Company Paid Holidays
- Parental Leave
- 401(k) Retirement Plan
- Group Term Life and Travel Assistance
- Voluntary Life and AD\&D Insurance
- Health Savings Account, Health Care \& Dependent Care Flexible Spending Accounts
- Transit and Parking Commuter Benefits
- Short\-Term \& Long\-Term Disability
- Tuition Reimbursement, Personal Development, Certifications \& Learning Opportunities
- Employee Referral Program
- Corporate Sponsored Events \& Community Outreach
- Care.com annual membership
- Employee Assistance Program
- Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)
- Position may be eligible for a discretionary variable incentive bonus
About Guidehouse
Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.
Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.
If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1\-571\-633\-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.
All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.
If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties.
*Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.*
Salary Context
This $113K-$188K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Guidehouse, 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 $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($150K) sits 31% below the category median. Disclosed range: $113K to $188K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Guidehouse AI Hiring
Guidehouse has 6 open AI roles right now. They're hiring across Data Engineer, AI/ML Engineer, AI Software Engineer, Data Scientist. Positions span New York, NY, US, Chicago, IL, US, Washington, DC, US. Compensation range: $124K - $216K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.
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