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Added 3 days ago
X
Head of AI and ML
Xplor
Remote, United States
- $275,000 to $290,000 USD / year
The role owns the science of evaluation across every agent, the predictive and decision models behind the shared agents (churn, demand, payment recovery, fraud), and the experiment design…
Added 9 days ago
M
Member of Technical Staff (Senior AI Security Researcher)
Microsoft
United States
- $119,800 to $261,000 USD / year
…threats and strengthen the security of products, services, and AI systems. AI is increasingly important to that mission as capabilities and threat models evolve. Within MRT, the AI Red Team…
Added 9 days ago
Postdoctoral Research Associate - AI for Lab Operations
Oak Ridge National Laboratory
Oak Ridge, TN
…operations tool development, AI-driven risk modeling, multi-agent AI workflows for incident prevention, and trusted RAG systems for safety compliance and real-time hazard evaluation. The…
Added 11 days ago
Senior AI/ML Research Engineer, Cloud AI Research and AI Rapid Response
Google
Mountain View, CA
As a Senior AI/ML Research Engineer, you are a technical driver and applied researcher. You will trade long-term operational maintenance for rapid pathfinding velocity, independently…
Added 12 days ago
Manager, Software Engineering - Agentic Assurance Platform
Invoca
Remote, United States
…tool calls, partner APIs, configuration, telephony timing, agent-to-agent collaboration, context modeling, and data delivery all have to work together, and any one of them can change on any…
Added 13 days ago
Senior AI Researcher
Assail, Inc.
Boston, NY · Boston, MA
This is a research role, not an applied ML role. You'll own original research on offensive security agents - how they reason, plan, use tools, and operate autonomously over long horizons.…
Added 16 days ago
2
Remote | Research Scientist - Computer Science & Computational Physics - $100–$400/hour
24-MAG
New York, NY
- $100 to $400 USD / hour
…problem-solving to contribute their knowledge to frontier AI research and evaluation…
Added 20 days ago
AI Researcher, AI.x
Charles Schwab
San Francisco, CA
As an AI Researcher within Schwab’s Artificial Intelligence Strategy & Transformation (AI.x) organization, you’ll operate at the intersection of advanced applied research and…
Added 20 days ago
Applied Researcher - Scientific AI
Prime Intellect
San Francisco, CA · New York City, NY
- Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
Added 20 days ago
Lead Applied Researcher - New York
Prime Intellect
New York City, NY
- A track record leading high-performing applied-research or research-engineering teams, deep credibility in RL/post-training/agents/evaluation/ML systems, exceptional recruiting judgment,…
Added 20 days ago
Applied Researcher - Ecosystem & Product
Prime Intellect
San Francisco, CA · New York City, NY
…excellent open-source and product experience. This role sits inside Applied Research and works deeply with engineering. You will build core open-source systems, shape researcher-facing…
Added 20 days ago
Applied Researcher - Computer Use
Prime Intellect
San Francisco, CA · New York City, NY
…outcome is actually complete. You will build post-training and evaluation systems for multimodal agents operating browsers, desktops, and cross-application workflows. The work is grounded…
Added 20 days ago
Applied Researcher - Quantitative Finance
Prime Intellect
San Francisco, CA · New York City, NY
- Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
Added 20 days ago
Applied Researcher - Robotics
Prime Intellect
San Francisco, CA · New York City, NY
…learning, control, world models, simulation, computer vision, agent evaluation, or production systems interacting with the physical…
Added 20 days ago
Applied Researcher - Chip Design
Prime Intellect
San Francisco, CA · New York City, NY
- Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops.
Added 20 days ago
Applied Researcher - Sovereign AI
Prime Intellect
San Francisco, CA · New York City, NY
- Relevant experience: RL/post-training, private ML systems, high-assurance evaluation, agent safety, regulated-domain ML, public-sector technical work, or deployment under strict data and…
Added 20 days ago
Applied Researcher - Continual Learning
Prime Intellect
San Francisco, CA · New York City, NY
- Relevant experience: continual or online learning, RL, meta-learning, memory systems, post-training data loops, adaptive production ML, or evaluation under changing distributions.
Added 20 days ago
Applied Researcher - Forward-Deployed RL
Prime Intellect
San Francisco, CA · New York City, NY
You will own applied RL programs from the first ambiguous customer problem through a deployed improvement loop. You will understand the workflow and business stakes, decide what can be…
Added 20 days ago
Applied Researcher - Agentic RL
Prime Intellect
San Francisco, CA · New York City, NY
…improve from experience. This is Prime's broad, cross-domain Applied Research role, focused on RL and ML systems. Your work should hold up across several application domains: algorithms,…
Added 22 days ago
Principal / Senior Solutions Engineer – Top-of-Stack & Agentic AI
Kelly Services
x, CA
This is a premier opportunity to serve as the leading technical voice at the frontier of applied enterprise artificial intelligence. The #1 feature of this opportunity is the opportunity to…
Added 22 days ago
M
Principal Security Researcher
Microsoft
WA · Redmond, WA · Redmond
- $142,800 to $304,200 USD / year
The MDASH team is advancing how organizations discover and resolve vulnerabilities in source code. MDASH uses a multi-agent, multi-model system to analyze code, validate whether potential…
Added 24 days ago
Applied Algorithms Researcher
Codegen
United States
Seeking Applied Algorithms Researcher for groundbreaking work in AI code generation at the forefront of GPT-4 technology. Ideal candidate is a pioneer in AI with academic and applied…
Added 24 days ago
AI Researcher
Arc
Remote, United States
Experience designing rigorous evaluation methodology - statistically sound benchmarking, synthetic data generation, or dataset curation - for non-deterministic systems.
Added 25 days ago
AI Research Post Doctoral Fellow
University of New Mexico
Albuquerque, NM
…Department of Computer Science, seeks a full-time Postdoctoral Researcher to lead development of an open-source agentic artificial intelligence platform as part of a federally funded,…
Added 25 days ago
Senior Applied Researcher
Apple
Cupertino, CA · San Francisco, CA · Seattle, WA
…recommendations to proactive intelligence and large-scale commerce systems, we are transforming how users discover, engage, and transact across the Apple ecosystem. The ASE AI/ML…

Invoca

Manager, Software Engineering - Agentic Assurance Platform

Remote, United States

Base Salary: $195,000–$275,000*

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Job details

Pay: Base Salary: $195,000–$275,000*
Posting language: English
Posted: Oct 2, 2026

Original job description

About Invoca Invoca is an AI-powered revenue execution platform that brings together marketing, commerce, and contact center teams to turn every customer interaction into measurable, profitable growth. Join our dynamic, fast-growing team, where innovation and collaboration are at the core of our culture.

About the Team Invoca's AI agents’ outcomes depend on much more than the model and harness: tool calls, partner APIs, configuration, telephony timing, agent-to-agent collaboration, context modeling, and data delivery all have to work together, and any one of them can change on any given day. In agentic systems, the hardest failures are quiet ones: an agent can report success while the booking, the lead, or the data never arrives. The Agentic Assurance Platform team builds the product that gives Invoca, and its customers, justified confidence that every agent deployment still works after something changes. It is a platform, not a QA function: a shared system that turns any change, on any surface, into a verdict backed by evidence. In practice that means APIs and a policy engine for release gates in CI, orchestration of simulated conversations across voice, messaging, web, agents, scorers and LLM judges calibrated against human review, live quality signals on production traffic, and checks that verify outcomes where they land, in the systems customers rely on. The team is new and moving fast, and its charter is broad: voice and messaging agents, and every agentic product Invoca ships as that portfolio grows.

About the Role We're hiring an Engineering Manager to lead the Agentic Assurance Platform team. You'll manage a growing team of engineers and own the platform's delivery, operational health, and growth, reporting to AI Engineering leadership. You'll join a new team with a clear mission and the chance to shape both the product and the team. Your job is to build assurance into a platform that every agent team at Invoca adopts by default: every agent-affecting change checked before it reaches customers, every live agent monitored, and every failure turned into a test so it cannot ship twice.

This is a management role with technical teeth. You'll work alongside an architect and a tech lead, so you won't be the primary author of the architecture, but you need the depth to hold a high bar in design reviews of distributed systems, APIs, data pipelines, and AI evaluation, and to earn the trust of senior engineers. Assurance adds hard calls of its own, such as what counts as evidence, when a sample is too small, and whether a judge can be trusted, so you'll need to stay close to the code, the traces, and the data.

What You'll Do Lead and grow the team

Manage, coach, and develop the engineers on the Agentic Assurance Platform team: clear expectations, honest feedback, real career growth.
Hire senior talent in a competitive market, and own candidate experience that top-tier passive candidates say yes to: tight loops, prepared interviewers, fast decisions.
Build a culture of ownership and craft, where engineers build for their users, measure what they ship, and use the agentic tools they build.

Own platform outcomes, not roadmap items

Run the platform as a product with internal users: set adoption and outcome goals (failures caught by automation first, time to detect, time to restore), instrument them, and measure whether teams ship faster and with more confidence because of your team's work.
Partner with Product, the agent platform and product teams, the teams that deploy agents for customers, and architects on roadmap and priorities, and represent the platform in R&D planning and launch readiness.
Make the platform self-serve: APIs, SDKs, CI integrations, shared scenario and policy formats, and reference implementations that let other teams add their own checks without waiting on yours.

Build the platform as a product

Build a platform that governs every way an agent's behavior can change, not only code: prompts, templates, model routes, tool contracts, configuration, and partner systems. Ship new gates in shadow mode, and earn the right to block.
Design for risk-based policy: a copy edit and a model swap get different evidence, sample sizes, and rollout, decided by policy the platform enforces rather than by a review meeting.
Keep the core small and stable: it owns contracts, policy, and evidence, while simulation, scoring, and observability engines plug in behind adapters, so swapping an engine never changes a verdict.

Run delivery with data

Own delivery health using DORA-style metrics and flow analysis, and manage flow and work in progress, not just effort.
Make delivery predictable: honest estimates, visible risks, no surprise slips.
Find where high-volume, low-difficulty toil concentrates, and automate it.

Build trust into the platform

Treat judges, simulators, test fixtures, monitors, and the gate itself as instruments, with calibration and health checks built into the platform. Missing evidence means "insufficient," never "pass."
Make the platform's numbers trustworthy: rates with confidence intervals, judge accuracy against human labels, and open doubts recorded alongside every verdict.
Make production-like testing a platform capability: isolated test environments on demand and realistic simulations that keep test traffic separate from customer data.
Embed operational rigor: platform SLOs, alerts that reach an owner, on-call health, honest postmortems, and a pipeline that turns every incident into a regression scenario. Partner with Security so access control, audit, and privacy keep pace with capability.

Champion the agentic development era

Make your own team the reference implementation of AI-assisted engineering: agentic coding workflows, automated review gates, AI in the SDLC as habit rather than demo.
Put agents to work inside the platform itself, generating scenarios, triaging failures, and finding coverage gaps, under the same gates as everything else.

What We're Looking For

8+ years in software engineering, including meaningful hands-on years building backend, distributed, data, or platform systems, and 3+ years managing engineers.
Experience leading a platform, infrastructure, or developer-experience team whose customers are internal engineers, with a track record of driving measurable adoption. Experience building evaluation, testing, or reliability infrastructure as a shared platform is a strong plus.
Working fluency in modern AI systems and how to evaluate them: LLM APIs and agents, tool calling with MCP or similar protocols, simulation, LLM-as-judge and its failure modes, tracing and telemetry. Enough depth to hold a technical bar in design reviews; you don't need to be a researcher.
Statistical judgment: comfortable with sampling, confidence intervals, and comparing a candidate against what's live, and able to explain why 30 passing runs isn't proof.
Systems thinking across boundaries: you've debugged failures that span services, third-party APIs, data pipelines, and configuration, and you know most production failures happen at the seams.
Data-driven delivery management: you've used DORA metrics or equivalent to find and fix real bottlenecks, and you understand flow.
Operational and security mindset: you've owned production services, run incident response, and treat auditability and the privacy of customer conversations as design requirements.
Demonstrated success hiring and retaining senior engineers.
Direct, calibrated communication with engineers and executives alike: honest characterization over spin, risks surfaced early, and clarity about what is known and what isn't.
High ownership in ambiguous, fast-moving territory.
A plus: experience with voice or conversational AI, telephony or contact-center systems, or regulated industries such as healthcare or financial services.

How Success Will Be Measured

Success in this role will look like:

The assurance platform is the default way agent teams ship: agent-affecting changes run through it, teams add their own checks self-serve, and platform telemetry, not anecdote, proves it.
Agent problems are caught by automation (a gate, a simulation, a live eval, or an alert) before they reach customers, and every agent-affecting change carries a recorded verdict, whatever surface it comes from.
Failures are detected fast, and each confirmed failure becomes a regression scenario within days, without a manual hand-off.
Every go-live is proven ready in isolated environments, and the quality numbers leadership and customers see are calibrated, with their uncertainty stated.
Delivery is predictable and measurably improving.
The team is retained, growing, and hiring well.

📍 Location: This is a remote-first role. We are currently hiring in the following locations: 📍 United States: Greater Los Angeles Area (including Santa Barbara and San Diego) · SF Bay Area · Denver Metro · Austin Metro · Chicago Metro · Greater NYC Area · Seattle Metro Candidates must be based within ~2 hour drive of these areas. Occasional business travel may be required.

Compensation, Benefits & Perks:

At Invoca, we believe great work starts with taking care of our people. That's why we offer competitive compensation and benefits designed to support your health, your family, your growth, and your life outside of work. For teammates in the U.S., health benefits begin on your first day of employment.

Compensation

Base Salary: $195,000–$275,000*
Variable Compensation: Bonus and/or commission eligibility, where applicable.
Equity: All employees are invited to share in Invoca's success through our stock option program.

*Actual compensation will depend on factors including experience, skills, and location.

Benefits & Perks

Health & Wellbeing

Day-One Health Benefits – Medical, dental, and vision coverage begins on your first day of employment for U.S.-based teammates.
Mental Wellbeing – Access to mental wellbeing support and an Employee Assistance Program (EAP).
Wellness Subsidy – Reimbursement that can be applied toward gym memberships, fitness classes, and more.

Time Away

Flexible Time Off – We encourage a healthy work-life balance. Our flexible paid time off policy gives you the flexibility to recharge and take time away when you need it.
Paid Holidays – Invoca provides 20 U.S. paid holidays, including a winter break, giving you time to rest, recharge, and spend time with friends and family.
Paid Family Leave – Up to 12 weeks of 100% paid leave for baby bonding, adoption, and caring for family members.*
Paid Medical Leave – Up to 12 weeks of 100% paid leave for childbirth and medical needs.*

Growth & Career

Enterprise-Grade AI Tools – Access to industry-leading enterprise AI tools, including leading LLMs and agentic AI workflow solutions to help you maximize productivity and work more effectively.
Professional Development – Annual reimbursement of up to $1,000 per fiscal year to support learning, certifications, conferences, and other professional development opportunities.

Financial Benefits

401(k) – Invoca offers a 401(k) plan through Fidelity with a company match of up to 4%.*

Recognition & Community

Recognition Programs – We celebrate great work through company-wide and team recognition programs, including President's Club and quarterly and departmental awards recognizing innovation, execution, and customer impact.
InVacation (Sabbatical) – As a thank-you to our long-term team members, we offer a sabbatical after seven years of service.

*Some benefits may vary for teammates outside the U.S. based on local laws, regulations, and country-specific offerings.