Product Engineer

Product Engineer at Epic Placements Product Engineer at Epic Placements in Jersey City, New Jersey Posted in 11 days ago.

Type:

full-time

Job Description:

Product Lead Engineer (AI Systems / 0

• 1) New York | In-Person (4-5 days/week) $150K
• 300K + Equity The Opportunity We're working with a venture-backed team building AI-native infrastructure for one of the most complex, high-friction systems in the U.S.: healthcare operations . This is not incremental optimization. They're rebuilding core workflows
• claims, billing, clinical documentation
• as end-to-end automated systems powered by LLMs, structured data pipelines, and human-in-the-loop feedback loops .

The problems are messy:

inconsistent inputs adversarial edge cases (payer rules, denials, compliance) real-world financial impact The upside is equally large: direct control over revenue flow ability to reshape cost structures in a $100B+ market systems that compound in performance over time The team includes engineers from top AI, quant, and systems backgrounds , and they're scaling aggressively post-Series A. The Role They're hiring a Product Lead Engineer to own a full problem space

• not a feature, not a service
• a domain . This is a hybrid role by design: Product ownership (defining what to build and why) Systems thinking (designing how it works end-to-end) Execution (shipping and iterating quickly) You'll take a workflow like: clinician input
• > structured data
• > payer interaction
• > cash collection .

..and turn it into a reliable, automated system with measurable performance. What You'll Actually Do Own a Domain End-to-End Define system boundaries, inputs/outputs, and failure modes Translate ambiguous workflows into structured, testable systems Ship iteratively with tight feedback loops Design AI + Systems Together Decide when to use models vs rules vs hybrid approaches Build feedback loops (human-in-the-loop, retraining signals, error correction) Optimize for accuracy, latency, and economic impact

• not just functionality Operate on Real Metrics Instrument systems around: claim success rates denial reduction time-to-payment Debug edge cases and continuously improve system performance What They're Looking For Core Profile Strong technical background (CS, math, physics, or similar) Experience building 0
• > 1 systems with real-world constraints Comfortable reasoning about: distributed systems data pipelines model behavior + failure modes High-Rigor Signals Background in quant, top-tier engineering teams, or highly technical startups Evidence of fast learning and high slope (rapid progression, outsized ownership) Ability to break down ambiguous problems into structured solutions Mindset You optimize for correctness and outcomes , not just shipping fast You're comfortable operating without clear specs You care about building systems that improve over time Why This Role Real technical depth•not CRUD apps, but complex, high-stakes systems Full ownership•you define and build, not just execute Tight feedback loops•your work directly impacts revenue + operations AI-native from first principles•not retrofitting legacy systems Clear trajectory•> Director-level ownership of a domain Who This Resonates With Ex-quants or engineers who want to apply rigor to real-world systems Builders who've done 0•> 1 and want more ownership People who enjoy messy, adversarial problem spaces Engineers who think in systems, not endpoints