Lead Product Manager, AI Agents

$180K - $240K San Francisco, CA, US Senior AI Agent Developer

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About This Role

AI job market dashboard showing open roles by category

About Us

Salient builds AI agents for regulated financial services. Our agents automate loan servicing, compliance, collections, recovery, insurance claims, and disputes for banks, captives, and specialty lenders.

We are:

  • Backed by a16z and Y Combinator, with $75M raised in Series A funding
  • Cash flow positive and profitable, with mid eight figure ARR achieved in under two years
  • Already serving more than 20% of the auto lending industry
  • Processing millions of real customer calls and transactions every day
  • Fully deployed in production with major financial institutions
  • Actively expanding into new financial services segments
  • Building together in person in San Francisco

We are deeply integrated with our customers, own the full technology stack, and move quickly to bring modern AI into regulated industries where precision, reliability, and performance matter.

The Role

We're hiring the Lead Product Manager for the agent product itself, omni-channel. You will own what the agent can do, how well it does it, and how quickly a new lender can get it live. This is the most important surface at the company, and today it's a set of very capable channels that needs to become one coherent product.

This is a hands-on role. You'll be listening to call recordings, sitting with servicing teams, writing specs an engineer respects, and defining what "good" means for an agent that talks to people about their money. You'll have the option to build a product team around you over time, but the first year is about your own judgment and throughput.

What You'll Own

  • The roadmap and strategy for the agent across voice, text, email, and chat — including the hard part: making a conversation that starts in one channel finish cleanly in another.
  • Agent quality. You define the metrics — containment, resolution rate, escalation, handle time, CSAT, error and hallucination rates — build the evaluation loop, and move the numbers.
  • The servicing workflow catalog. Turning payments, payoffs, hardship, collections, title, and insurance from bespoke deployments into configurable product.
  • Time-to-live. Getting a new lender from signed to in-production faster every quarter.
  • Guardrails and compliance posture in the product: disclosures, audit trails, human handoff thresholds, and the design decisions that keep us inside FDCPA, TCPA, UDAAP, and state servicing rules.
  • The bar for discovery, specs, and instrumentation that the rest of the product org will inherit.

What We're Looking For

  • You've shipped LLM-powered products to real users — not demos. You can reason about prompting, evals, retrieval, tool use, and latency/cost tradeoffs, and you know where models break.
  • You own outcomes, not artifacts. You move fast, decide with incomplete information, and are comfortable being the most accountable person in the room.
  • You go to the source. You'll listen to hundreds of calls and sit with ops teams because that's where the real workflow lives.
  • You're rigorous about measurement. You can tell a model problem from a product problem from a data problem.
  • You hold your own with engineers. You can read a trace, debate an architecture decision, and write a spec that doesn't need translating.
  • You have instincts for risk. You know how to design a system that's allowed to be wrong sometimes without that being catastrophic.
  • You can say no to a large customer and keep the relationship.
  • You write and present clearly enough to stand in front of a lender's risk committee.

Nice to Have

  • Voice, IVR, contact center, or conversational AI experience — telephony constraints, barge-in, latency budgets, transcription error, call QA.
  • Background in lending, servicing, collections, or adjacent financial operations.
  • Experience hiring or mentoring product managers.

Why This Role

Most AI product roles are features bolted onto an existing business. This is the product. The agent is the company, the market is enormous and underserved, and the problems are genuinely hard — real-time voice, regulated conversations, and a quality bar set by people's mortgages and car payments. You'll have the scope to define how an entire industry talks to its customers.

At Salient, we’re building at the edge of AI - fast, focused, and with real ownership. Sprints and major launches move quickly, and we look for people who are energized by that pace. Our team typically works around 60 hours per week, beginning at 8:00 AM, with four days spent collaborating in person at our San Francisco office.

We also offer a benefits package designed to support our full-time employees: medical, dental, and vision coverage, a generous 401(k), and catered lunches.

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Compensation Range: $180K - $240K

Salary Context

This $180K-$240K range is above the median for AI Agent Developer roles in our dataset (median: $190K across 12 roles with salary data).

View full AI Agent Developer salary data →

Role Details

Company Salient
Title Lead Product Manager, AI Agents
Location San Francisco, CA, US
Experience Senior
Salary $180K - $240K
Remote No

About This Role

AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.

Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.

Across the 8,943 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Salient, this role fits into their broader AI and engineering organization.

AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.

What the Work Looks Like

A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.

AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.

Skills in Demand for This Role

Python (16% of roles) Aws (9% of roles) Azure (7% of roles) Rag (6% of roles) Gcp (5% of roles) Pytorch (5% of roles) Claude (4% of roles) Kubernetes (4% of roles)

Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.

The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?

Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.

Compensation Benchmarks

AI Agent Developer roles pay a median of $214,400 based on 180 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. Disclosed range: $180K to $240K.

Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.

Salient AI Hiring

Salient has 1 open AI role right now. They're hiring across AI Agent Developer. Based in San Francisco, CA, US. Compensation range: $240K - $240K.

Location Context

AI roles in San Francisco pay a median of $263,811 across 2,416 tracked positions. That's 24% above the national median.

Career Path

Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.

From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.

Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.

What to Expect in Interviews

Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.

When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.

AI Hiring Overview

The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.

The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).

AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.

The AI Job Market Today

The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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

Based on 180 roles with disclosed compensation, the median salary for AI Agent Developer positions is $214,400. Actual compensation varies by seniority, location, and company stage.
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
About 6% of the 8,943 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Salient is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Agent Developer positions include AI Architect, Principal Engineer, Head of AI Engineering. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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