Top Remote Jobs in Portland, ME

Lead a small AI engineering team while remaining hands-on in research and production software development. Build agentic capabilities for monitoring, guardrailing, evaluation, collaboration, and security. Perform exploratory data analysis, feature engineering, model fine-tuning, prototyping, and technical design. Translate AI research into scalable product features, set technical direction, mentor engineers, and deliver reliable production code.

Develop and optimize generative AI architectures for material and molecular discovery, including diffusion models, flow matching, and GFlowNets. Integrate reward signals from learned predictors and simulations, manage data ingestion and quality control, develop computational workflows, and deploy production-grade ML capabilities. Collaborate with ML researchers, computational scientists, engineering, product, and R&D teams. The role requires expertise in applied ML, scalable frameworks, cloud platforms, and material discovery, with preferred experience in active learning, Bayesian optimization, guided generation, and agentic or LLM methods.

Build production-ready agentic AI capabilities focused on monitoring, guardrails, evaluation, security, quality, and human-agent collaboration. Perform machine learning tasks including exploratory data analysis, feature engineering, and model fine-tuning. Translate research into scalable software, rapidly prototype features, collaborate cross-functionally, and explore emerging agentic technologies.

Leads GM Insurance’s regulatory and statistical reporting processes, including reporting inventories, filing calendars, data analysis, validation, reconciliation, controls, documentation, and submissions. Partners with Legal, Accounting, Actuarial, Claims, Product, Operations, Technology, and Data teams to resolve data issues, support audits and regulatory inquiries, improve data quality, and automate reporting processes. Requires advanced SQL, Python experience, insurance reporting knowledge, and strong analytical and stakeholder-management skills.

Apply advanced actuarial methods, predictive modeling, and data analytics to support reserving, ratemaking, and business decisions. Build and validate models, perform EDA, query and transform data, create visualizations, mentor junior analysts, lead projects, and collaborate with cross-functional teams to drive performance and perform periodic reserve reviews.

An 8-month Strategic Account Manager program preparing participants for dealer account management at GM Financial. Responsibilities include building dealer relationships, supporting automotive finance programs, analyzing dealer data, resolving credit and funding issues, identifying portfolio and compliance risks, and representing the GM Financial brand. The role requires travel, weekend availability during training, relocation after completion, and a valid driver's license.

The Senior IT QA Engineer owns quality strategy and outcomes across complex technology initiatives. Responsibilities include designing automated testing solutions, integrating quality verification into CI/CD pipelines, analyzing quality and production data, developing dashboards, managing risk, leading root-cause analysis, and influencing product, engineering, architecture, security, operations, and business stakeholders. The role requires technical contributions across web, mobile, API, data, cloud, and distributed systems, plus mentoring engineers and advancing quality engineering practices.

Reviews delinquent mortgage files to determine foreclosure referral eligibility and ensure compliance with CFPB, federal, state, local, and investor requirements. Audits documentation, prepares regulatory correspondence, manages referral files, communicates with borrowers, resolves outstanding issues, supports audits, and updates procedures based on regulatory changes. Requires mortgage servicing and loss mitigation experience, knowledge of FHA, VA, FNMA, and FHLMC requirements, strong organization, communication, analytical, and problem-solving skills.

Lead product, cloud, application, infrastructure, and internal security across Hipp’s healthcare SaaS platform. Responsibilities include architecture reviews, threat modeling, vulnerability management, cloud and identity security, monitoring, incident response, AI-agent security, compliance controls, vendor risk, customer security reviews, and security mentorship.

Designs, operates, and improves cloud and infrastructure security across AWS and multi-cloud environments. Responsibilities include cloud governance, identity and access controls, network security, infrastructure as code, CI/CD and software supply-chain security, container and Kubernetes security, monitoring, threat modeling, incident response, and security automation. The role also contributes to AI security initiatives involving LLMs, AI agents, and MCP integrations, communicates risks across teams, leads complex initiatives, and mentors engineers.

Own system-level testing for Lance and LanceDB across correctness, reliability, scalability, performance, data integrity, fault recovery, upgrades, and compatibility. Build automated test frameworks, realistic workloads, fault-injection scenarios, performance and soak tests, and reproducible CI environments. Investigate failures using logs, metrics, traces, and source code, create minimal reproductions, and partner with engineers on fixes. Apply AI tools responsibly to accelerate test development, failure analysis, and debugging.

Own the strategy, roadmap, and success metrics for AI security capabilities across the Pathfinder platform. Serve as the internal expert on agentic AI threats, identity security, and emerging attack techniques. Define requirements for securing AI agents, MCP servers, and orchestration frameworks; conduct market and competitive research; lead design partner programs; coordinate cross-portfolio product work; and support analyst, customer, marketing, and pre-sales engagements.

Design and build production agentic AI systems and internal automation workflows across business functions. Responsibilities include prioritizing high-impact automation, developing multi-step and multi-agent workflows, integrating agent platforms, implementing human-in-the-loop controls, improving reliability and observability, evaluating performance, and shaping reusable AI engineering patterns. The role requires collaboration with nontechnical stakeholders and ownership of ambiguous problems from definition through measurable business impact.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Leads implementation and adoption strategy for enterprise transformation initiatives, partnering with business and technology teams from solution design through deployment and stabilization. Assesses stakeholder impacts, readiness, behavioral changes, risks, and adoption metrics; develops deployment, training, communications, and sustainment plans; equips leaders and sponsors; removes barriers; and captures reusable practices. The role requires influencing executives and frontline teams across business, technology, learning, communications, and operational functions.

Leads end-to-end business analysis for U.S. Department of Veterans Affairs systems, including requirements elicitation, documentation, user stories, process models, acceptance criteria, and traceability. Serves as the liaison between business stakeholders and technical teams, supports Agile ceremonies, manages Jira backlogs, performs impact analysis, supports testing and UAT, and mentors other analysts. Ensures solutions comply with VA security, accessibility, privacy, and delivery standards.