Jobs at Mitratech

The Senior Software Engineer will focus on Machine Learning model development, data management, model deployment, and staying updated on NLP advancements.

Lead technical direction for data platform capabilities: design and maintain data pipelines, reporting models, and data governance to support trusted metrics and AI/LLM agentic workflows. Drive architectural improvements, mentor engineers, collaborate on roadmaps, and represent technical capabilities externally.

Lead end-to-end AI product work across Mitratech's shared AI platform and customer experiences. Set strategy and roadmap, convert ambiguous problems into shipped, enterprise-grade features, partner with engineering and design, prioritize based on customer feedback, and represent products to senior stakeholders and customers.

Lead technical direction for a major product domain, reduce architectural debt, mentor engineers, standardize AI-agent workflows, and design scalable backend solutions integrating LLMs and cloud services. Drive cross-team RFCs, cookbook standards, and adopt agentic AI tooling while balancing security, quality, and delivery.

Lead and scale a global Talent Acquisition function across regions, design a standardized operating model, drive digital transformation and AI/automation in recruiting, manage multi-regional teams, ensure compliance and DEIB strategy, own ATS optimization and analytics, and support full-cycle recruiting for senior roles.

Lead end-to-end learning design and development: conduct needs analyses, define strategy and metrics, create scripts/storyboards, build interactive eLearning in Articulate, package SCORM/xAPI modules, manage LMS, evaluate impact, and mentor L&D peers while partnering with SMEs and HR leaders.

Lead end-to-end learning design and development: perform needs analysis, define strategy and success metrics, create scripts/storyboards, build interactive eLearning in Articulate Storyline and Rise, publish SCORM/xAPI modules, configure LMS, produce multimedia assets, manage SMEs, evaluate program impact, and maintain QA and development standards.

Design, build, and operate end-to-end LLM-powered agents and RAG architectures on an AWS-native GenAI platform. Own services (FastAPI), MCP servers, Terraform IaC, evaluation pipelines, reliability practices, and mentor engineering teams while collaborating with product, data, and platform stakeholders.

Lead Customer Success and retention for background screening clients, driving product adoption, renewals, up-sell, and operational improvements. Partner cross-functionally with Product, Compliance, Operations, and Sales, manage global retention teams, integrate acquired teams, and serve as executive escalation for critical accounts. Use analytics (TAT, accuracy, churn, NPS) to inform strategy.

Lead and build the AI Quality & Governance platform: observability, evaluations, guardrails, SLOs, and incident playbooks. Design automated and human-in-the-loop evaluation pipelines, enforce release gates, translate governance frameworks into engineering controls, partner with product teams on AI incidents, and hire and grow a hands-on engineering team while contributing substantial production code.

Lead end-to-end design of complex enterprise SaaS features, using AI-native tools to drive discovery, interaction design, prototyping, and design-system contributions. Collaborate with product and engineering, mentor designers, advocate for users, and deliver implementation-ready outputs that influence product strategy.

First-line support for customers via phone, chat, email, and web portal. Troubleshoot, research, and resolve issues within SLA, document interactions, and meet monthly customer satisfaction goals.

Lead strategy, design, and delivery of a Legal Managed Bill Review product with an AI-first mindset. Define roadmap, write requirements, partner with engineering and data teams, track success metrics, and drive stakeholder and client engagement. Manage a distributed agile team, promote AI-assisted tooling, and align go-to-market and adoption strategies while ensuring compliance, configurability, and operational reliability.

Hands-on full-stack Product Manager owning end-to-end delivery for ATS products across two Scrum teams. Write detailed requirements, manage backlogs, run sprint ceremonies, remove blockers, collaborate with stakeholders, apply customer and market research, define success metrics, and iterate with engineering and QA to drive adoption and business outcomes.

Lead and scale a global Talent Acquisition function across regions, build and mentor multi-regional teams, drive process optimization and AI/automation adoption, own ATS strategy (e.g., Greenhouse), develop TA analytics and DEIB recruiting strategy, partner with HR and business leaders on workforce planning, and perform senior full-cycle recruiting as needed.

Design, build, and operate production-grade generative AI systems: multi-agent orchestration, end-to-end RAG pipelines, LLM evaluation and integration, scalable AWS-based AI infrastructure, CI/CD for models, observability, data validation, and evaluation frameworks to ensure quality, attribution, and resilience.