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we are looking for a AI Engineer (Mid-Senior).
What You'll Do:
- Build and harden AI Workers for real enterprise workflows - procurement, finance, HR, sales, risk, integration.
- Own the MCP connector framework - reusable tool servers that power every AI Worker.
- Design multi-step agentic flows with planning, reflection, retries, approvals, and clean failure modes.
- Ship evaluation suites that catch regressions before customers o.
- Instrument cost, latency, and reliability; drive them down relentlessly.
- Partner with Product and Solutions to ship features that survive contact with enterprise reality.

we are looking for a Automation Architect.
What You'll Do:
- Architect complex multi-system automations - OCR pipelines, Priority ↔ Salesforce sync, multi-carrier shipping, e-commerce ↔ ERP invoicing, reconciliation flows.
- Lead technical scoping for large Professional Services engagements.
- Build reusable process blueprints (we already have 116; you'll add the next 30).
- Troubleshoot the hardest production incidents - data, timing, auth, edge-cases in legacy systems.
- Mentor the PS team; review workflow designs; raise the architectural bar.
- Close the loop with Product on connector gaps, platform limitations, and feature requests.

we are looking for a Frontend Engineer.
What You'll Do:
- Build and evolve the Workflow Builder, Tables, and App Maker UIs - visual, drag-and-drop, real-time, collaborative.
- Design and ship the Gini AI Worker dashboards - run visualization, step traces, approvals, cost tracking.
- Own performance - sub-second interactions, optimistic updates, virtualized lists, edge-first rendering.
- Partner tightly with design + product on component systems, accessibility, and motion.
- Contribute to our design system - reusable, themable, keyboard-first.

we are looking for a Machine Learning Engineer.
What You'll Do:
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.

we are looking for a Solutions Architect.
What You'll Do:
- Own end-to-end solution design for enterprise deals - from first discovery call to signed SOW to production handoff.
- Lead technical discovery with CIOs, CTOs, and IT leads. Map their current stack (Priority / SAP / NetSuite / Salesforce / custom) and design the Engini blueprint.
- Architect multi-system integrations - ERP ↔ CRM ↔ e-commerce ↔ shipping ↔ AI Workers - using Engini's MCP-native connector framework.
- Run live technical demos and POCs that prove value in days, not months.
- Partner with Sales on pricing, scoping, and risk assessment; be the "technical closer" on 6-7 figure deals.
- Partner with Product - bring real-world field signals back and influence the roadmap.
- Mentor the Professional Services team on architectural patterns and reusable process blueprints.

We're looking for a Product Manager to own the operational efficiency aspect of the platform end to end. This is both a strategy and an execution role: you'll decide what execution responsibilities the product would expand to and be in the details with engineering and design shipping it. The hard part isn't building a workflow - it's knowing which work a customer will genuinely hand to an agent, and what has to be true before they will.
What You'll Do:
Define human and agent interaction models: Shape how users collaborate with AI agents, from user initiated queries and agent driven outreach to seamless side by side execution.
Lead agentic ticket resolution and IAM automation: Own the end to end product strategy for identity tasks, including provisioning and deprovisioning, entitlement changes, plus joiner, mover, and leaver workflows.
Own the agentic execution layer: Spec the core product rails for executing actions in customer environments, including human approval flows, risk controls, and confidence building mechanisms.
Drive field to roadmap feedback loops: Partner closely with customer facing and POC teams to translate real world edge cases and customer insights into scalable roadmap features.

We're looking for a Product Manager to own the data and knowledge component of the platform end to end. This is both a strategy and an execution role: you'll decide what execution responsibilities the product would expand to and be in the details with engineering and design shipping it. The hard part isn't building a workflow - it's knowing which work a customer will genuinely hand to an agent, and what has to be true before they will.
What You'll Do:
Architect the Data Fabric: Own the data layer, defining schemas and cross relationships across IAM, network, and security domains to power agent capabilities.
Lead the Knowledge Layer: Own how policies and operating procedures are captured, structured, and updated so agents apply them reliably.
Build the Customer Experience: Partner with design and engineering to build user interfaces for data exploration, search, reporting, and connection health.
Scale Data Fabric and Knowledge as a Platform: Own the internal interface between data layers and other product components to feed agent visibility and decision making.
Drive Field to Roadmap Feedback Loops: Partner closely with customer facing and POC teams to turn real world field signals into scalable product features.

We are looking for a Legal Operations Manager to own how agreements move through the company. This is a hands-on legal operations role. You'll own the contract lifecycle end to end: intake, triage, routing to external counsel where needed, tracking, signature, filing, and follow-through on what we committed to. You will maintain our templates and playbooks, keep the contract tracker and reporting accurate, support compliance and customer security reviews, and use legal tech and AI tools to keep the work moving. You will also improve how it works.
What You'll Do:
Own the contract lifecycle end to end: intake, triage, routing to external counsel where needed, tracking, signature, filing, and follow-through on commitments.
Maintain company templates and playbooks.
Keep the contract tracker and reporting accurate.
Support compliance and customer security reviews.
Use legal tech and AI tools practically to keep work moving.
Continuously improve how legal processes work.

We are looking for an AI Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
Youll design, build, and ship the AI systems behind Alex: production agents that reason over customer identity data, call real tools, and complete IAM tasks end to end. Starting from a cybersecurity need, youll frame the technical problem, choose an approach, and own the solution through production: architecture, implementation, evaluation, deployment, and iteration on real customer behavior.
Youll build on our companys shared agent infrastructure and extend it: new tools and integrations, workflow orchestration, context and memory management, evaluation harnesses, and the guardrails that keep an autonomous agent safe inside a customers environment.
This is a hands-on engineering role, not a research position. The goal is not to prove that an idea can work; it is to make it useful, reliable, and observable for customers in production.
What You'll Do:
Design, implement, and ship AI-powered features for complex cybersecurity workflows, from prototype to production.
Build the systems that make agents work in practice: tool integrations, planning and orchestration logic, context management, structured outputs, and recovery from failures.
Choose the right technical approach for each problem, combining models, deterministic logic, data, and conventional software where appropriate.
Define quality for each use case and build the evaluation pipelines that measure correctness, task completion, consistency, safety, latency, and cost, and wire them into CI and release.
Debug agent behavior in production: trace failures to their root cause in the prompt, tool, data, or architecture, and fix it.
Own the reliability, observability, and cost of the agent systems you build.
Collaborate with cybersecurity experts, product, and platform engineers throughout development.