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About This Role
About Bering Straits Professional Services, LLC
Bering Straits Professional Services (BSPS) is committed to world\-class management of global logistics, training and procurement services for U.S. Government agencies. BSPS is certified by the U.S. Small Business Administration (SBA) as an 8(a) contractor (https://www.sba.gov/federal\-contracting/contracting\-assistance\-programs/8a\-business\-development\-program). In February 2022, BSPS became an International Organization for Standardization (ISO) 9001 certified company. BSPS received the ISO 9001 quality standard certification through the Performance Review Institute (PRI).
About this position: AI Software Engineer Location – Anchorage, AK
The Essential Duties and Responsibilities are intended to present a descriptive list of the range of duties performed for this position and are not intended to reflect all duties performed within the job. Other duties may be assigned. To perform this job successfully, an individual must be able to satisfactorily perform each essential duty. The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the position.
Applicants will be notified via phone or email within ten (10\) business days of submittal.
Essential Duties \& Responsibilities
- Responsible for designing, developing, and implementing AI\-powered capabilities using Large Language Models (LLMs) across LogIT applications within the portfolio.
- Responsible for developing and integrating conversational interfaces, copilots, and intelligent assistants into logistics and operational systems.
- Responsible for building and maintaining retrieval\-augmented generation (RAG) pipelines leveraging enterprise data sources, documents, and knowledge bases.
- Responsible for implementing prompt engineering techniques, guardrails, and orchestration workflows to ensure accurate and secure AI outputs.
- Responsible for integrating AI capabilities into existing systems using APIs, microservices, and middleware.
- Responsible for collaborating with Product Owner(s), system engineers, and stakeholders to support implementation of AI use cases across the portfolio.
- Responsible to attend and participate in daily team meetings, execute assigned workload, and work within project management tools i.e. JIRA, Confluence, etc.
- Responsible for supporting monitoring, evaluation, and observability of LLM performance and usage.
- Responsible for adhering to security, data governance, and Responsible AI standards.
- Responsible for contributing to reusable AI components and shared engineering practices.
Required (Minimum Necessary) Qualifications
- Education Requirements: Must have a bachelor’s degree or 5\-10 years’ equivalent experience.
- Level of Experience Requirements: Three (3\)\-Five (5\) years of software engineering experience.
- Experience developing applications using modern programming languages (e.g., .NET, Python, Java, or similar).
- Experience integrating or working with LLM APIs (e.g., Azure OpenAI, OpenAI, Google Gemini).
- Hold or have the ability to acquire a government security clearance; requires U.S. citizenship.
Knowledge, Skills, Abilities, and Other Characteristics
- Knowledge of LLM concepts including prompt engineering, embeddings, and retrieval\-augmented generation (RAG).
- Knowledge of APIs and microservices\-based system integration.
- Familiarity with cloud\-based AI platforms.
- Ability to develop AI\-enabled features within LogIT and enterprise systems.
- Ability to analyze and translate technical and business requirements into functional AI solutions.
- Ability to evaluate AI outputs and apply improvements for accuracy and reliability.
Preferred
- N/A
Supervisory Responsibilities
- This position will not have supervisory responsibilities.
DOT Covered/Safety\-Sensitive Role Requirements
- This position is not subject to federal requirements regarding Department of Transportation “safety\-sensitive” functions.
Necessary Physical Requirements
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this role. Employees must always maintain a constant state of mental alertness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
Essential and marginal functions may require maintaining physical condition necessary for bending, stooping, sitting, walking or standing for prolonged periods of time; most of time is spent sitting in a comfortable position with frequent opportunity to move about.
Work Environment
The work environmental characteristics described here are representative of those that must be borne by an employee to successfully perform the essential functions of the role. Employees must always maintain a constant state of situational awareness. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
Job is performed in an office setting with exposure to computer screens and requires extensive use of a computer, keyboard, mouse, and multi\-line telephone system. The work described herein is primarily a modern office setting. Occasional travel may be required.
Additional Qualifying Factors
As a condition of employment, you will be required to pass a pre\-employment drug screening and have acceptable background check results. If applicable to the contract, you must also obtain and maintain the appropriate clearance levels required and must also be able to obtain access to military installations.
Shareholder Preference
BSNC gives hiring, promotion, training, and retention preference to BSNC shareholders, shareholder descendants and shareholder spouses who meet the minimum qualifications for the job.
*Bering Straits Native Corporation is an equal opportunity employer. All applicants will receive consideration for employment without regard to any status protected by state or federal law, or any other basis prohibited by law.*
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Bering Straits Native Corporation, 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 $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Bering Straits Native Corporation AI Hiring
Bering Straits Native Corporation has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Anchorage, AK, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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