# Senior Software Engineer, Applied AI

**Company:** [PrizePicks](https://hotfix.jobs/companies/prizepicks)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $175k – $185k/yr
**Experience:** 6+ years
**Skills:** Python, LLMs, Machine Learning, Agent Orchestration, Tool Calling, RAG, Embeddings, Search Retrieval, Distributed Systems, APIs, Observability, Prompt Management, Model Monitoring, Evaluation Harnesses, Inference Optimization
**Posted:** 2026-08-18

> Build and ship production Applied AI capabilities, including agent infrastructure, RAG services, evaluation systems, and AI-powered engineering workflows. The role requires 6+ years of software engineering experience, strong backend and distributed-systems skills, and direct experience delivering LLM- or ML-powered products.

## Job Description

## Responsibilities

### Build the Agent Platform and Tooling
- Design and implement orchestration, tool/function calling, evaluation harnesses, prompt/version management, tracing/observability, and safety/guardrails.
- Support retrieval-augmented generation (RAG), structured extraction, and production inference workflows.

### Operationalize AI in the SDLC
- Embed AI into engineering workflows, including code review assistance, test generation, incident support, and developer copilots.
- Establish quality gates and measure impact.
- Determine which work to delegate to agents versus retain as human work, and scope tasks so agents can succeed.

### Ship Applied AI Features End-to-End
- Own projects from prototype through production, including data needs, system design, model/vendor selection, rollout plans, monitoring, and iteration.
- Partner with product, design, and data/ML stakeholders to deliver customer-facing outcomes.

### Diagnose and Drive AI Adoption
- Diagnose AI adoption bottlenecks and failure modes across teams.
- Build missing capabilities, teach existing tools, and advocate for adoption.

### Mentor and Set Engineering Standards
- Establish practices for reliability, evaluation, incident response, privacy/security, and AI development.
- Coach engineers through design reviews, pairing, and technical leadership.
- Help engineers critically review AI-generated code.

## Requirements
- 6+ years of professional software engineering experience or equivalent, including shipping production systems.
- Direct experience on an Applied AI or product AI team building LLM- or ML-powered features; agent or tooling experience is strongly preferred.
- Demonstrated judgment in agent-driven development, including delegation, agent scoping, context management, and output verification.
- Strong backend and systems design skills, including APIs, distributed systems, queues/workflows, observability, and performance.
- Ability to navigate ambiguity and drive outcomes with product, design, data/ML, and platform partners.
- Track record of mentoring peers and improving engineering quality.

## Nice to Have
- Experience building platform capabilities for engineers, such as SDKs, internal frameworks, or developer tooling.
- Practical experience with embeddings, search/retrieval, evaluation methodologies, and model monitoring.
- Experience building AI-powered tooling or products such as agents and assistants at scale.
- Familiarity with inference constraints, including latency, cost, and caching; vendor/model tradeoffs; and deployment patterns.

## Example Projects
- Agent orchestration layer with tool routing, policy guardrails, and traceability.
- RAG service with document ingestion, chunking/indexing, evaluation, and freshness controls.
- AI-in-SDLC rollout with automated pull-request review feedback and test-plan suggestions.
- Team-wide evaluation harness with goldens, regression tests, offline scoring, and online experimentation.
- Organization-wide AI adoption diagnostic and tooling-gap remediation plan.

## Compensation and Benefits
- Typical salary range: **$175,000–$185,000 USD annually**.
- Company-subsidized medical, dental, and vision plans.
- 401(k) plan with company match.
- Annual bonus.
- Flexible paid time off.
- Paid leave programs, including 16-week paid parental leave and disability benefits.
- Workplace flexibility and modern work schedules.
- Company-wide in-person events and team outings.
- Lifestyle enhancement program.
- Company-provided equipment, with Windows and Mac options.
- Annual performance reviews and career development opportunities.

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