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Job summary

Design and build RAG architectures and production LLM-powered features for document understanding and extraction. Own the MLOps pipeline, including model versioning, monitoring, and the implementation of safe rollout mechanisms.

Job details

We are the only AI Native documents intake automation platform serving the claims and litigation industries. Founded in 2019 by a team of lawyers and data scientists, we processes millions of documents each month for hundreds of US law firms, including many of the largest and most respected plaintiff and injury law firms in the country. We're looking for a Senior AI/ML Engineer to help expand our next-generation document intelligence system. Working in close collaboration with our Data Science team, you'll bring deep technical rigor to a system that gets smarter with every document it digests, across hundreds of customers at scale. The system draws on a combination of ML, LLM, RAG, applied mathematics, and smart algorithm design to deliver results at a high level of accuracy. What you will be doing: -Retrieval-Augmented Generation: Design and build RAG architectures for document understanding, classification, and extraction, from chunking and indexing through retrieval quality and grounding. -LLM Feature Development: Ship production LLM-powered features end-to-end, from prompt design through evaluation, not just prototypes. -Evaluation-Driven Development: Build regression suites, confidence calibration methods, and evaluation frameworks that make AI output quality measurable. -Collaboration with Data Science: Partner closely with our Data Science team to bring research-grade techniques into production. -ML Pipeline & MLOps: Own model, data, and prompt versioning; build reproducible pipelines for ingestion, training, evaluation, and serving. -Rollout Automation & A/B Testing: Implement canary deployments, side-by-side A/B testing, and rollback mechanisms for safe model and prompt releases. -Monitoring & Observability: Implement drift detection, data quality monitoring, and alerting; define SLOs for model and pipeline health. -System Architecture & Leadership: Design secure, high-performance ML infrastructure; evaluate tooling (Bedrock, MLflow, Airflow); mentor engineers and influence best practices. What you will be need: -Experience: 5+ yrs in software engineering, with 2+ yrs focused on ML/AI in production systems. -LLM & RAG Fundamentals: Hands-on experience with prompt engineering, RAG architectures, and evaluation-driven development, with a track record of shipping LLM-powered features real users rely on. -MLOps & Pipeline Tooling: Practical experience with model, data, prompt versioning, experiment tracking, and deployment automation; proficiency with Airflow, MLflow, and Bedrock or equivalents. -Programming: Proficient in Python; comfortable with SQL and data engineering patterns. Benefits -Medical | Blue Cross Blue Shield Multiple PPO plan options with nationwide coverage 100% in-network preventive care Comprehensive coverage for doctor visits, prescriptions, and mental health -Dental | Guardian 100% coverage for preventive care 80-90% coverage for basic services 50-60% coverage for major services Orthodontia benefit up to $2,000 -Vision | Guardian VSP $10 exam copay, $20 materials copay $150 allowance for frames or contacts every 12 months -Life Insurance | Guardian Company-paid life insurance of $50,000 for all full-time employees -Voluntary Life Insurance | Guardian Option to purchase additional coverage for yourself, your spouse, and dependents Spouse coverage up to 50% of employee amount, child coverage up to $10,000 -401(k) Retirement Plan Employer match of 50% of employee contributions, up to $2,350 per year Immediate eligibility upon hire and full vesting from day one -Discretionary Paid Time Off (PTO) Take time as needed to recharge and balance personal responsibilities No fixed accrual - focused on results and trust -Paid Holidays 10 paid company holidays annually, including major U.S. holidays and year-end break Email Your Resume In Word To Nitu.Gulati-Pauly@cybercoders.com Looking forward to receiving your resume through our website and going over the position with you. Clicking apply is the best way to apply. Please do NOT change the email subject line in any way. You must keep the JobID: linkedin : NNG-1990757L402 -- in the email subject line for your application to be considered. Nitu Gulati-Pauly - VP of Client Development This is a new role. This job was first posted by CyberCoders on 06/28/2026 and applications will be accepted on an ongoing basis until the position is filled or closed. Everforth CyberCoders is proud to be an Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law. Our hiring process includes AI screening for keywords and minimum qualifications. Recruiters review all results. Everforth CyberCoders will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable state and local law, including but not limited to the Los Angeles County Fair Chance Ordinance, the San Francisco Fair Chance Ordinance, and the California Fair Chance Act. Everforth CyberCoders is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. If you need special assistance or an accommodation while seeking employment, please contact a member of our Human Resources team to make arrangements. Copyright © 2026 Everforth, Inc. All rights reserved.

What you’ll do

Design and build RAG architectures and production LLM-powered features for document understanding and extraction. Own the MLOps pipeline, including model versioning, monitoring, and the implementation of safe rollout mechanisms.

Requirements

Requires over 5 years of software engineering experience with at least 2 years focused on production ML/AI systems. Proficiency in Python, SQL, and hands-on experience with RAG, prompt engineering, and MLOps tooling is essential.

Benefits

• Medical Insurance • Dental Insurance • Vision Insurance • Life Insurance • Voluntary Life Insurance • 401(k) Retirement Plan • Discretionary Paid Time Off • Paid Holidays

Listed skills

• SQL · Preferred
• prompt engineering · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• LLM
• RAG
• MLOps
• Prompt Engineering
• Airflow
• MLflow
• Amazon Bedrock
• Data Engineering
• Model Versioning
• A/B Testing
• Drift Detection
• System Architecture
• Evaluation-Driven Development
• Document Intelligence

Job areas

• Software
• Technology
• Data & Analytics
• Engineering
• Legal