Forward Deployed Engineer

Mid · Full Time

San FranciscoUSD 150k – 170k2w ago
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Role

What you'll do.

As a Forward Deployed Engineer at AKASA, you'll lead the end-to-end deployment and optimization of generative AI solutions for healthcare revenue cycle management. This role combines software engineering with AI/ML expertise, requiring you to design LLM evaluation frameworks, manage production deployments, and collaborate with R&D teams to deliver comprehensive solutions for top-tier health systems like Cleveland Clinic and Johns Hopkins. You'll need 3+ years of Python experience, expertise in LLM evaluation methodologies, and proficiency with relational databases and modern DevOps tools.

Responsibilities

  • Execute End-to-End Deployment Implementation: Lead the complete lifecycle of new AI model deployments for healthcare clients, encompassing requirements analysis, technical configuration, comprehensive testing protocols, production rollout coordination, and ongoing production health monitoring. Ensure seamless integration with existing healthcare systems while maintaining data integrity and compliance standards.
  • Design and Own LLM Evaluation Frameworks: Architect and implement sophisticated evaluation frameworks to continuously measure and improve large language model performance across customer deployments. Establish both offline evaluation methodologies and online production monitoring systems to track model quality metrics, accuracy rates, and business impact. Document evaluation results and recommend optimizations to enhance clinical accuracy and documentation completeness.
  • Technical Client Onboarding and Integration Support: Partner with client engagement teams to guide healthcare organizations through technical onboarding processes, API integration setup, troubleshooting complex integration issues, and data acquisition workflows. Serve as the technical bridge between clients and internal teams, ensuring smooth deployments and rapid issue resolution in production environments.
  • Contribute Product and Platform Feedback: Gather actionable insights from customer deployments and production implementations to inform product strategy and platform improvements. Identify gaps in current solutions, document enhancement requests, and collaborate with product management to prioritize features that deliver maximum value for healthcare revenue cycle operations.
  • Collaborate with R&D Engineering Teams: Work closely with internal R&D engineering teams to architect robust, scalable client solutions that leverage the latest generative AI capabilities. Participate in technical design reviews, contribute to system architecture discussions, and ensure deployed solutions maintain production stability while accommodating customer-specific requirements.

Qualifications

What we look for.

Technical

  • Python Programming Expertise

    3+ years of professional Python development experience with demonstrated proficiency in writing production-grade code, working with data structures, implementing algorithms, and building maintainable software solutions.

  • LLM Evaluation and Measurement

    Hands-on experience designing and executing both offline and online LLM evaluation frameworks. Proficiency in establishing model performance metrics, quality measurement methodologies, and continuous monitoring systems for large language models in production environments.

  • Relational Databases and Data Management

    Comfortable working with SQL-based relational databases, designing database schemas, writing complex queries, and optimizing data retrieval patterns. Experience with data normalization and relational design principles.

  • API Design and Integration

    Experience designing and consuming RESTful APIs, understanding API architecture patterns, implementing API integrations, and troubleshooting integration issues between systems.

  • ETL Pipeline Development

    Proficiency with Extract, Transform, Load (ETL) pipeline development and orchestration. Ability to design data workflows, handle data quality issues, and implement automated data processing pipelines.

Education

  • Bachelor's Degree in Computer Science or Engineering

    A bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related field is required. This foundation provides essential knowledge in algorithms, data structures, software design principles, and computer architecture.

Experience

  • Professional Software Development

    3+ years of professional experience in software development or related engineering roles, demonstrating proficiency in building production systems and working effectively within engineering teams.

  • Production System Deployment Experience

    Experience managing the deployment lifecycle of applications to production environments, including configuration management, testing strategies, rollout procedures, and production support activities.

Skills

Required

  • Python Programming

    Professional-grade Python development with strong fundamentals in language features, common libraries, and best practices for production code.

  • LLM Evaluation Methodologies

    Expertise in designing comprehensive evaluation frameworks for large language models, including metric selection, benchmark creation, and performance assessment techniques.

  • SQL and Relational Databases

    Proficiency with SQL query writing, database design principles, schema optimization, and working with relational database systems.

  • REST APIs

    Experience designing, integrating, and troubleshooting RESTful APIs and understanding API-based system architectures.

  • Data Pipeline Development

    Capability to design and implement ETL processes, data orchestration, and automated data workflows.

  • Technical Communication

    Exceptional communication and interpersonal skills with meticulous attention to detail—critical for translating complex technical requirements and ensuring healthcare system deployments meet exacting compliance and accuracy standards.

Preferred

  • FastAPI Framework

    Nice to have

    Experience building modern, high-performance Python web applications using FastAPI for API development and rapid prototyping.

  • SQLAlchemy ORM

    Nice to have

    Proficiency with SQLAlchemy for object-relational mapping, database abstraction, and Pythonic database interactions.

  • PostgreSQL

    Nice to have

    Experience with PostgreSQL database system, including schema design, query optimization, and advanced SQL features.

  • Docker Containerization

    Nice to have

    Hands-on experience containerizing applications with Docker, creating Dockerfiles, and managing container-based deployments.

  • Kubernetes Orchestration

    Nice to have

    Knowledge of Kubernetes for container orchestration, deployment management, and scaling applications in production environments.

  • Amazon Web Services (AWS)

    Nice to have

    Familiarity with AWS cloud services including compute, storage, and networking solutions commonly used in enterprise deployments.

  • GitHub Actions CI/CD

    Nice to have

    Experience with GitHub Actions for continuous integration and continuous deployment pipelines, automating testing and deployment workflows.

  • Healthcare Data Standards

    Nice to have

    Knowledge of healthcare data exchange standards such as FHIR (Fast Healthcare Interoperability Resources), HL7 (Health Level 7), and EDI (Electronic Data Interchange) for healthcare system integrations.

  • React Frontend Development

    Nice to have

    Basic to intermediate React experience for building user interfaces and front-end components in full-stack healthcare applications.

Tech stack

Languages

Python

Frameworks

FastAPISQLAlchemyReact

Databases

PostgreSQLRelational Databases (General)

Tools

DockerKubernetesAWS (Amazon Web Services)GitHub ActionsGit/GitHub

Other

LLM Evaluation FrameworksETL PipelinesFHIR / HL7 / EDI StandardsGenerative AI / LLM Technologies

Compensation

Pay and benefits.

Base·USD 150,000 – 170,000

Equity·Stock options

Benefits

  • Flexible Paid Time Off (PTO)

    Flexible vacation policy enabling you to manage work-life balance and take time off as needed without rigid constraints.

  • Comprehensive Health Insurance Coverage

    Expansive coverage for medical, dental, and vision insurance, ensuring comprehensive healthcare protection for you and your family.

  • Health Savings Account (HSA) Contributions

    Employer contributions to Health Savings Accounts, providing tax-advantaged healthcare savings and financial flexibility.

  • Generous Parental Leave Policy

    Comprehensive paid parental leave supporting both childbirth and adoption, enabling you to focus on family priorities during critical periods.

  • Full Life Insurance Coverage

    Employer-paid life insurance for all employees, providing financial security and peace of mind for your family.

  • Home Office Stipend

    Financial support for setting up a productive remote work environment, covering equipment and office supplies.

  • Cell Phone and Internet Reimbursement

    Reimbursement for personal cell phone and internet expenses, recognizing the necessity of staying connected while working remotely.

  • Company-Paid Holidays

    Paid holidays throughout the calendar year, ensuring time off for major holidays and celebrations.

  • 401(k) Retirement Plan

    Tax-advantaged retirement savings plan with employer matching to support long-term financial planning and retirement security.

Process

Interview steps.

  1. 01

    Technical Screening Call

    Initial conversation with a recruiter or hiring team member to discuss your background, experience with Python, LLM evaluation methodologies, and general fit for the role. This 30-minute call focuses on your professional history and interest in healthcare AI applications.

  2. 02

    Coding and Technical Assessment

    Structured technical evaluation assessing Python proficiency, problem-solving abilities, and understanding of database concepts. This may include code implementation exercises, SQL query writing, and technical architecture questions relevant to deployment and LLM evaluation systems.

  3. 03

    System Design and Deployment Discussion

    Technical interview exploring your experience with deployment architectures, ETL pipelines, API design, and scalable system design. Expect questions about production deployment strategies, monitoring approaches, and how you've handled complex integration challenges.

  4. 04

    LLM Evaluation and Product Sense Interview

    Discussion of your experience designing LLM evaluation frameworks, measuring model quality, and understanding healthcare use cases. This round assesses your ability to think critically about AI model performance in production healthcare environments.

  5. 05

    Stakeholder and R&D Engineering Collaboration Interview

    Conversation with engineers from the R&D team to assess collaboration style, communication skills, and ability to work effectively across technical teams. Expect discussion of previous experiences collaborating with product teams and managing technical stakeholder relationships.

  6. 06

    Leadership and Culture Fit Discussion

    Final interview with a member of leadership to discuss career goals, alignment with AKASA's mission in healthcare AI, and cultural fit. This conversation focuses on your values, communication style, and commitment to high-quality execution in a fast-growing healthcare AI startup.

Full posting

Original listing.

About AKASA

At AKASA, our mission is to build the future of healthcare with AI. As the leading provider of generative AI solutions for the healthcare revenue cycle, we help health systems comprehensively capture and communicate the full patient clinical journey. By empowering health systems to streamline their operations, they can focus on what matters most - delivering quality patient care. We have raised over $205M in funding from investors such as Andreessen Horowitz, BOND, and Costanoa Ventures.

This is the most exciting time to join AKASA. Revenue bookings for our new AI-native product suite have grown over 20x since launching in 2024. In this time, we have broken our record for the largest deal in company history three times consecutively. This growth is driven by the massive improvement we are generating for our customers across clinical quality and documentation accuracy, both top priority areas for health system leaders.

Our deployments have been recognized nationally as "one of the most comprehensive real-world uses of GenAI in healthcare finance to date" (link). Our customer base represents more than $120B+ in net patient revenue and includes the most innovative health systems in the country, like Cleveland Clinic, Duke, Stanford, and Johns Hopkins.

Some of our recent recognitions include being named one of America's Top Startup Employers 2026 by Forbes, #1 most promising healthcare RCM startup of 2025 by Black Book Market Research, and one of the fastest-growing GenAI startups to watch by AIM Research. Our CEO was ranked among the “Top 50 Healthcare Technology CEOs” by the Healthcare Technology Report, and we have been certified as a “Great Place to Work” for the past 6 years in a row.

We’re building on this momentum to redefine what’s possible in healthcare. We’re looking for exceptional people to help us accelerate that reality.

About the Role

As a Forward Deployed Engineer, you’ll deliver client deployments that empower healthcare revenue cycle teams to work faster, more accurately, and with greater insight. You will work on the lifecycle and deployment of the ML models that power our products.

You’ll work closely with client engagement, product, and R&D teams to ensure smooth deployments, ongoing production stability and expansion of our deployment platform.

What You'll Do

  • Execute implementation tasks for new deployments — from requirements analysis to configuration, testing, rollout, and support of production health.

  • Work with client engagement teams to guide customers through technical onboarding, integration setup, troubleshooting, and data acquisition

  • Build and own evaluation frameworks to continuously measure and improve LLM performance across customer deployments

  • Contribute feedback and insights that shape product and platform improvements

  • Work closely with R&D engineering teams to build robust scalable client solutions

Skills & Qualifications

  • Bachelor's degree in Computer Science, Engineering, or similar

  • 3+ years of professional Python experience

  • Experience designing and running LLM evals (offline and online) to measure model quality and performance.

  • Comfortable working with relational databases, APIs, and ETL pipelines

  • Strong communication and interpersonal skills with meticulous attention to detail

Nice to haves

  • Familiarity with FastAPI, SQLAlchemy, Postgres.

  • Proficiency in Docker, Kubernetes, AWS.

  • CI/CD experience with GitHub Actions.

  • Experience with healthcare data exchange (FHIR, HL7, EDI)

  • Frontend experience (React)

What We Offer

  • Flexible paid time off (PTO)

  • Expansive coverage for health, dental, and vision

  • Employer contribution to Health Savings Accounts (HSA)

  • Generous parental leave policy

  • Full employee coverage for life insurance

  • Home office stipend

  • Cell phone/internet reimbursement

  • Company-paid holidays

  • 401(K) plan

Compensation

  • Based on market data and other factors, the salary range for this position is $150,000-$170,000 + Equity. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors

We’re committed to doing the best work of our lives, together. Come see if we're the right team for you.

AKASA is a proud equal opportunity employer and we believe that a diverse and inclusive workforce is an imperative. We welcome people of different backgrounds, genders, races, ethnicities, abilities, sexual orientations, and perspectives, just to name a few. We do not discriminate based upon any protected class and we encourage candidates of all identities and backgrounds to apply. AKASA considers qualified applicants regardless of criminal histories in accordance with the San Francisco Fair Chance Ordinance.

AKASA is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].

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