Senior Forward Deployed Engineer, AI Studio

This is a fully remote position, open to applicants in United States.

📋 Description

• Spearhead the discovery process by elucidating business workflows, user roles, desired outcomes, value hypotheses, acceptance criteria, constraints, data readiness, dependencies, and production implications.

• Convert intricate challenges into actionable solution designs, delivery strategies, technical workstreams, estimates, milestones, risks, acceptance criteria, release methodologies, and support transitions.

• Construct, prototype, assess, or contribute to essential production components, including AI-driven applications, RAG, bounded agents, intelligent automation, APIs, and integrations.

• Establish and uphold integrated architecture across applications, workflows, data and knowledge pipelines, models, retrieval systems, agents, APIs, enterprise integrations, identity management, access controls, observability, and human review processes.

• Coordinate delivery efforts among engineering, data science, machine learning, testing, platform, security, compliance, and business teams.

• Create integrated testing, AI evaluations, and governance frameworks with explicitly defined release thresholds.

• Facilitate production readiness through CI/CD, staged releases, monitoring, logging, service level objectives (SLOs), rollback procedures, recovery plans, runbooks, and controlled deployments.

• Assist with early issue triage, stabilization, and the transition to the operational owner.

• Clearly communicate evidence, risks, trade-offs, and project status.

• Assess adoption and value, transforming delivery insights into reusable components, accelerators, standards, documentation, and playbooks.

⛳️ Requirements

• A Doctorate degree with 1 year of experience in Computer Science, IT, or a related discipline, OR a Master’s degree with 8–10 years of experience, OR a Bachelor’s degree with 10–12 years of experience, OR a Diploma with 12–14 years of experience.

• Proficient in technical discovery, workflow analysis, feasibility studies, data and integration readiness assessments, success measurement, estimating, and dependency mapping.

• Expertise in enterprise solution architecture and integration across applications, APIs, services, data, models, retrieval systems, agents, workflows, identity management, security, and enterprise systems.

• Proficient in production-level Python and SQL.

• Familiarity with classical machine learning and natural language processing.

• Knowledge of foundation-model integration, prompt and context management, RAG, structured output, provenance, citations, bounded tool usage, permissions, recovery, and human oversight.

• Experience with evaluation, quality assurance, safety, privacy, validation, auditability, Responsible AI, and GxP controls.

• Knowledge of cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged releases, rollback procedures, incident response, disaster recovery, capacity planning, FinOps, runbooks, and MLOps/LLMOps.

• Proven end-to-end technical ownership of at least one production AI, ML, software, data, or automation solution that delivers a measurable enterprise outcome.

• Experience in designing or reviewing production software, APIs, services, data flows, evaluation pipelines, and enterprise integrations.

• Capability to translate complex business challenges into technical designs, actionable delivery plans, acceptance criteria, and production-readiness evidence.

• Advanced expertise in at least one area including Applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps.

• Advanced knowledge of RAG, knowledge and agent systems, including hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement, and adversarial testing.

• Familiarity with AWS, Bedrock or SageMaker, Databricks, Spark, Kubernetes, serverless or event-driven systems, infrastructure as code, MLflow, Airflow, Kubeflow, observability, and FinOps.

• Experience with JavaScript or TypeScript, modern web applications, API gateways, distributed workflows, process automation, document or vision processing capabilities, and human-AI review experiences.

• Background in life sciences, biotechnology, pharmaceuticals, healthcare, GxP, or validated systems is preferred.

• Strong critical thinking, technical leadership, communication skills, sound judgment, ownership, and resilience.

🏝️ Benefits

• Comprehensive employee benefits package.

• Retirement and Savings Plan featuring generous company contributions.

• Group medical, dental, and vision coverage.

• Life and disability insurance.

• Flexible spending accounts.

• Discretionary annual bonus program.

• Stock-based long-term incentives.

• Award-winning time-off policies.

• Flexible work models where feasible.

• Opportunities for career development.

• Support for work/life balance.