Applied AI Jobs

Pay

$130k–$180k (base, US)

Distinct from

Unlike an ML engineer or data scientist, this role builds no models; it is a people-and-process role focused on getting existing AI tools adopted, closer to enablement/L&D than to engineering.

Source: Juniper Square AI Enablement Lead posting (Built In, remote US), $130K-$180K

Source refreshed: the original Axios posting (Built In NYC 8919109) was removed on Apr 15, 2026. The role is now widely posted and established; live US base bands cluster around $130K-$190K (Juniper Square $130K-$180K, Ridgeline $170K-$190K, IANS $144K-$180K), with senior/staff roles reaching higher (Grainger $164K-$295K). Pay anchored to the Juniper Square posting, which matches the enablement definition: AI-fluency training on Claude and Cowork, curriculum development, coaching, and adoption measurement.

Pay

Pay not disclosed

Distinct from

Unlike a forward-deployed-engineer (who embeds inside one enterprise customer's environment for weeks or months) or an ai-integration-engineer (who connects AI to a single enterprise's internal systems), this role builds the identity, auth, and agent-linking rails that let many external, unaffiliated websites and services become part of an open agent ecosystem: platform partner engineering for a many-to-many ecosystem, not single-account embedding or internal integration.

Source: Harvey careers, Sr. AI Enablement Engineer

OpenAI has stood up a distinct 'Agent Enablement' function, this AI Deployment Engineer posting plus a parallel Full Stack Software Engineer, Agent Enablement posting, to grow an open ecosystem of agent-enabled partner sites and services (jobright.ai's mirror describes the mandate as owning 'the technical partner journey for priority agent enablement integrations, from use-case selection and readiness assessment through architecture, prototype, implementation, evaluation, launch, rollout, and ongoing maintenance'). Official posting: https://openai.com/careers/ai-deployment-engineer-agent-enablement-san-francisco/ (title and team confirmed to exist via web search and two independent mirrors; the page itself returned a 403 to automated fetch, so it is cited here for reference rather than as the primary source). Pay is deliberately omitted: third-party mirrors disagree sharply ($120K-$160K per one estimate, ~$238K per tryremotely.com, $197K-$280K per jobright.ai), none is a confirmed quote of OpenAI's own disclosed range, and per the no-fabrication policy an unverifiable number is worse than none.

Pay

$154k–$220k (base, US)

Distinct from

Unlike ai-enablement-lead (a people-and-process L&D role that trains employees and measures adoption but builds nothing), this is a hands-on engineering role that builds the internal tooling, MCP connectors, and governed AI stack employees use. Unlike ai-tooling-engineer (customer- and developer-facing product tooling at a platform vendor), the customer here is the company's own workforce. Unlike ai-integration-engineer (production integrations between an AI product and enterprise business systems), the remit is broad internal enablement and governance rather than a product's integration surface.

Source: Harvey 'Sr. AI Enablement Engineer' (remote US), $153,500-$220,300, harvey.ai careers

Pay is the range displayed on Harvey's own careers page for the Sr. AI Enablement Engineer posting: '$153,500 - $220,300 USD' (fetched directly 2026-08-22; the page renders the posting mirrored from Harvey's Ashby board, jobs.ashbyhq.com/harvey/393b91ff-9966-4a22-a39b-f49014965693). Multi-company signal: Ramp posted the same archetype as 'AI Operations Specialist | Enablement' (deploy dozens of AI-driven automations across non-engineering teams, coach internal AI champions; Built In req 8132921, removed Jul 14, 2026, and since retitled 'AI Operations Specialist | Agentic Workflows' on Ramp's Ashby board, jobs.ashbyhq.com/ramp/63df0ffc-bdc6-40ba-906f-fe03378536b0, no salary disclosed), and Glassdoor now tracks 'AI Enablement' as its own title (average $137,846, P25-P75 $106,112-$181,499, June 2026, 2 reports only so treated as weak corroboration). Dedup note: OpenAI's agent-enablement-engineer (tracked) is external partner-ecosystem engineering, a different scope; this role is internal-workforce enablement. Titles in this cluster have not fully hardened (Enablement Engineer vs Operations Specialist), which is why maturity is 'emerging' and confidence is moderate.

Pay

$160k–$310k TC (total comp, US)

Distinct from

Differs from a classic MLOps/DevOps engineer in that the system under management is a probabilistic agent, not a deterministic service, so the job centers on evals, traces, and guardrails rather than uptime alone.

Source: Fieldguide 'Software Engineer, AgentOps' (Y Combinator, SF/Remote US), $160K-$310K

Source upgraded from a market-aggregate taxonomy to a real, explicitly-titled posting: Fieldguide 'Software Engineer, AgentOps' (Y Combinator), $160K-$310K. The posted range is base plus equity and the exact split is not stated; the broader market varies widely (Integrate 'Agentic Operations Engineer' $135K-$175K; Revelation Pharma 'DevOps/AgentOps Engineer' $115K-$125K).

Pay

$160k–$220k (base, US)

Distinct from

Unlike agentops-engineer, where cost and latency monitoring is one of several observability/reliability duties inside a broader agent-runtime job, the AI FinOps Engineer's entire remit is the financial/economics layer: token-level unit economics, cost allocation, budgeting, and forecasting across AI workloads, a specialization pulled from cloud FinOps discipline rather than from SRE/agent-ops. Also distinct from ai-governance-lead (policy/risk, not cost) and ai-gateway-engineer (routing infrastructure, not cost accounting).

Source: Cargill 'AI Platform FinOps Sr. Engineer' (Bengaluru), careers.cargill.com

New addition (no existing tracked id). Directly fetched and re-verified the Cargill posting myself; it resolves and the quote above is verbatim from that page ('Owns end-to-end problem areas, including design, implementation, and adoption' is a second, paraphrased-from-fetch line describing scope, not re-quoted here to avoid stitching fragments). Corroborated by a second live, directly-fetched posting: Singtel Group 'AI FinOps Engineer #AIDA' (https://groupcareers.singtel.com/job/AI-FinOps-Engineer-AIDA-Sing/1327804166/), verbatim: 'Maintain the centralized framework for tracking Azure consumption and GenAI token usage across projects, teams, and applications' and 'Build dashboards and alerts to monitor real-time and forecasted costs, including anomaly detection for budget risks.' Neither Cargill nor Singtel discloses pay. Pay ($160K-$220K USD base, NYC) is sourced instead to a third, US-based, first-party posting: Bloomberg 'AI & LLM Infrastructure FinOps Analyst' (731 Lexington Ave, NYC, job #18395, https://bloomberg.avature.net/careers/JobDetail/AI-LLM-Infrastructure-FinOps-Analyst/18395). IMPORTANT CAVEAT: direct WebFetch attempts to that Bloomberg URL, its LinkedIn mirror, and a wallstreetcareers.com mirror all failed to load for me (404 / bot-blocked), so I could NOT independently re-fetch that raw page myself; the responsibilities and the '$160,000 - $220,000 USD Annual + Benefits + Bonus' figure come from consistent search-engine snippets across three separate queries (one confirming the exact NYC office address), which is a materially weaker evidentiary basis than the Cargill/Singtel pages I fetched directly. Flagging for the validator to attempt its own fetch of the Bloomberg posting before trusting the pay figure; if it cannot resolve either, the pay field should be dropped and the entity kept unpaid (like ai-tooling-engineer / ai-gateway-engineer in the baseline). General 'FinOps Engineer' salary aggregates (ZipRecruiter ~$84K-$135K, Glassdoor ~$93K-$166K) exist but are generic cloud-FinOps, not AI-specific, and were deliberately NOT used to avoid misattributing a non-AI figure. Maturity marked 'emerging': this is a newly-forming specialization splitting off from cloud FinOps specifically for AI/token economics, first appearing in postings in 2026.

Pay

$86k–$145k (base, US)

Distinct from

Unlike a general software or automation engineer, the emphasis is business-process diagnosis and low-code/agentic orchestration ('you do not need to be a deep coder'), not building bespoke application code.

Source: SailPoint AI Workflow Architect posting (Built In, removed Aug 5, 2026; $86K-$145K range still displayed)

Source posting status change (2026-08-22): the cited SailPoint posting was removed on Aug 5, 2026; the Built In page still resolves and still displays the '$86,300 - $145,494.00' US range alongside the removal notice, so the pay band remains documented but is no longer a live opening. The title continues to appear in the market (e.g. MW Partners 'AI Workflow Architect, Business Operations', San Jose, on behalf of a global multimedia and creativity software company, no salary disclosed). Pay band retained pending a new salaried first-party posting; flagged as sourced from a removed posting.

Pay

$155k–$246k TC (total comp, US)

Distinct from

Less deeply embedded than a forward-deployed engineer: an AI solutions engineer owns integration and deployment of a vendor product across many accounts, closer to pre-sales and post-sales solutions work than to writing production code inside one customer's stack for months.

Source: Google Solutions Engineer compensation, Levels.fyi ($155K L3 to $246K L5)

Pay anchored to Levels.fyi total-comp for the Solutions Engineer ladder (Google) as the closest resolvable primary datapoint; AI-specific solutions-engineer postings (e.g. per KORE1) fall in a comparable $130K-$260K band.

Pay

$171k–$295k TC (total comp, US)

Distinct from

Unlike a solutions architect or sales engineer, the FDE actually writes and ships production code inside the customer's stack rather than advising or demoing; frontier labs (OpenAI, Anthropic) pay 2-3.5x Palantir's classic FDSE at senior levels, almost entirely in equity.

Source: Palantir Forward Deployed Software Engineer compensation, Levels.fyi ($171K-$295K, median ~$211K)

Pay is total compensation (base + stock + bonus) per Levels.fyi for Palantir's FDSE title, the canonical origin of the role.

Pay

$185k–$245k (base, US)

Distinct from

Positioned as the successor to the prompt engineer: instead of crafting single prompts, it engineers the retrieval, memory, and tool context around the model, which is a genuine software-architecture discipline.

Source: Context Engineer salary analysis (May 2026): US senior-IC base $185K-$245K, frontier-lab total comp above $500K

Pay updated from the original approximate Glassdoor-derived band ($130K-$220K) to a 2026 context-engineer-specific analysis: US senior-IC base $185K-$245K, with staff total comp exceeding $400K and frontier-lab (OpenAI, Anthropic) total comp above $500K. Anthropic and OpenAI now hire 'Context Engineer' explicitly, and the role sits in the highest-paid cluster of the new AI engineering disciplines. Sourced from a May 2026 salary analysis (secondary); a single authoritative posting series is still forming, so the figure is flagged for review.

Pay

$130k–$250k (base, US)

Distinct from

Unlike an AgentOps engineer (who runs agents in production observability) or a context engineer (who builds the retrieval and memory environment), the eval engineer builds the measurement systems, harnesses, and graders that judge whether models and agents are good enough to ship.

Source: Distyl AI 'AI Evaluation Engineer' posting (SF/NY), $130K-$250K

Posted range $130K-$250K (basis not explicitly stated; read as base for an SF/NY IC engineer). Total comp for the discipline runs $230K-$650K+ (JobsByCulture 2026 career guide), with frontier labs at the top (Anthropic Research Engineer, Model Evaluations $320K-$485K; Magic MTS Evals $200K-$550K; Microsoft AI Evaluations Engineering). A distinct, fast-forming discipline.

Pay

$114k–$220k (base, US)

Distinct from

Overlaps with the AI eval engineer (who builds eval infrastructure) and the AgentOps engineer (who observes agents in production); the agentic QA engineer focuses on pre-release testing strategy and quality gates that decide whether an agent is fit to ship. Distinctness from the eval engineer is the main review question.

Source: Fieldguide 'AI Engineer, Quality (Evals)' (SF/Remote US), $170K-$220K

Pay: Fieldguide AI Engineer, Quality (Evals) $170K-$220K (LangSmith, Langfuse); Realign Agentic QA Engineer about $114,617 (Dallas). Many current postings are India-based (EXL, Weekday AI). EXL's QA Engineer (C1) Agentic AI describes the role well: testing strategies for LLMs, multi-agent and RAG systems, automated eval pipelines, and CI/CD quality gates.

Pay

Pay not disclosed

Distinct from

Differs from context-engineer (which curates retrieval and prompt context for models): this role builds the actual tools and MCP servers agents call. Differs from ai-conversation-designer (which designs conversational flows): this is developer-facing tooling infrastructure.

Source: Supabase 'AI Tooling Engineer' (remote)

Supabase's AI Tooling Engineer builds MCP servers, agent skills, and the dashboard assistant with an eval-first approach. No public salary range disclosed; pay omitted rather than estimated.

Pay

Pay not disclosed

Distinct from

Differs from agentops-engineer (runtime observability of agents) and ai-solutions-engineer (customer-facing integration): this is core infrastructure, the multi-provider routing and failover layer between applications and model providers.

Source: Vercel 'Software Engineer, AI Gateway' (SF/NYC), greenhouse.io

Vercel AI Gateway is a shipping product (one key for hundreds of models, unified API, automatic cross-provider failover). Pay not disclosed on the posting, so pay omitted. The original Built In URL did not resolve; source refreshed to the official Vercel greenhouse posting.

Pay

$134k–$200k (base, US)

Distinct from

Unlike ai-solutions-engineer (pre-sales, consultative, customer-facing), this is a pure engineering role building and maintaining production integrations. Unlike forward-deployed-engineer (embedded at customer sites), this can be internal-facing. Unlike ai-workflow-architect (higher-level design), this is hands-on implementation.

Source: Harvey 'Integration Engineer' official Ashby posting

Source refreshed 2026-08-22: the previously cited remotematchers.com mirror now shows 'This job is expired' (while still displaying the 'USD 133,500 - USD 200,300' range), but Harvey's official Ashby board carries a live 'Integration Engineer' posting, so the source is upgraded to the first-party URL. The Ashby page is JS-rendered and did not yield its salary text to automated fetch this round, so the pay band is retained from the mirror's displayed figures pending validator confirmation; flagged approximate. Salesforce's Sr. AI Integration Architect (Agentforce) reaches $173K-$260K. General integration-engineer median is about $100K-$154K (PayScope 2026); the AI-specific role commands a premium.

Pay

$82k–$186k (base, US)

Distinct from

Unlike a prompt engineer or context engineer (who engineer the model's retrieval and system context), the conversation designer owns the interaction layer: how the agent talks, what actions it takes, and how multi-turn flows feel to the user.

Source: UKG 'Conversation Systems Designer - AI Agent Behavior' (Seattle), $129,500-$186,100

Pay spans Checkr AI Conversation Designer $82K-$102K up to UKG Conversation Systems Designer $129,500-$186,100 (7+ years experience). Related 'AI Trainer' roles (RLHF and data labeling) are distinct and often lower-paid contract work.

Pay

$95k–$180k (base, US)

Distinct from

Unlike a security engineer (who secures infrastructure) or an AI eval engineer (who measures general quality for shipping), the AI red teamer adversarially attacks deployed models to surface safety, bias, and security vulnerabilities before real adversaries do.

Source: Handshake 'AI Red Teamer, Cybersecurity' (Seattle), $130K-$180K

Pay spans junior to senior: Handshake AI Red Teamer (Cybersecurity) $130K-$180K and (LLM Generalist) $95K-$145K; 10a Labs junior $70K-$90K. Frontier-lab AI safety and red-team roles pay far more. The role is borderline between AI operations and security research; included because it secures deployed AI systems.

Pay

$320k–$485k (base, US)

Distinct from

Unlike ai-red-teamer (offensive probing to find vulnerabilities), this role owns the full defensive lifecycle: designing, building, shipping, and maintaining production safety systems and enforcement infrastructure. Unlike ai-governance-lead (policy), this is hands-on engineering.

Source: Anthropic 'Software Engineer, Safeguards' (greenhouse.io), $320K-$485K

Pay $320,000-$485K base confirmed across multiple boards (greenhouse.io, jobsbyculture, jobera). Frontier-lab (Anthropic) defensive safety engineering: production guardrails, abuse-detection infrastructure, and enforcement tooling. The London equivalent pays 240K-325K GBP.

Pay

$150k–$230k (base, US)

Distinct from

Unlike a generic product manager, the AI PM requires fluency in model capabilities, evaluation, and agentic system design, and owns AI-specific risks (hallucination, eval-driven release gates, model and vendor tradeoffs) rather than pure feature delivery. Distinctness from generic PM is the main review question for this emerging-roles catalogue.

Source: KORE1 AI Product Manager Salary Guide 2026 ($150K-$230K base; $250K-$550K total comp senior)

Pay per KORE1 2026 guide: $150K-$230K base, $250K-$550K total comp at senior. Corroborated by postings: Schwab Sr AI Product Manager $220K-$280K; Avant Generative AI Product Manager $165K-$185K; Scale AI Product Manager, Gen AI. More mainstream than the other entries; included as a distinct AI-era specialization, but whether it belongs in an emerging-roles catalogue is the review question.

Pay

$184k–$219k (base, US)

Distinct from

Unlike a general GRC or privacy officer, this role governs probabilistic AI systems specifically (model risk, evals, agent behavior) against AI-specific regulation, and increasingly reports risk directly to executive leadership.

Source: Axial Search AI governance salaries analysis (median $169,000; senior-IC P25-P75 $184K-$219K)

Pay refreshed 2026-08-22: Axial Search's analysis was updated (insights page 'Updated: August 4, 2026') and now covers 1,997 US postings since January 2026 (was 146). The previously cited middle-80% band ($156K-$219K, median $158,750) is no longer published; the current headline is 'The median AI governance salary is $169,000.' The companion salaries page's percentile table gives IC (Senior) P25-P75 of $184,000-$219,000, IC (Mid) P25-P75 of $135,000-$235,000, and Manager P25-P75 of $212,000-$265,000 (median $244,000); the full posted range runs from $66,000 (P5, junior IC) to $330,000 (P95, C-suite). Pay band set to the senior-IC P25-P75 as the closest match to this lead-level entry; flagged approximate because the band is a percentile slice of posted ranges, not offers. Director and VP roles reach higher.