Forward Deployed Engineer (Data, ML & AI)

Forward Deployed Engineer (Data ML & AI)

Location: Remote Timezone: NA/Eastern Type: Full-time Experience: 10 Years

Role Overview

This position requires a Forward Deployed Engineer (FDE) specializing in Data Machine Learning and AI to embed directly within customer environments. You will serve as the primary technical authority transforming complex data challenges and operational bottlenecks into production-grade data pipelines machine learning systems and agentic AI solutions.

The role is heavily customer-facing: you will work alongside client business units and engineering teams to rapidly assess legacy data estates build scalable modern data platforms and deploy custom GenAI/LLM workflows that drive measurable business velocity. This is a high-ownership hands-on role where you will leverage Spec-Driven Development (SDD) and AI-assisted workflows to build refactor and demonstrate immediate value directly where the customer operates.

Key Responsibilities

• Customer Embedding & Data Delivery: Deploy directly into customer environments to understand their domain logic underlying data pipelines and architectural constraints. Own end-to-end deliveryfrom data discovery and schema design to pipeline deployment and model integrationbuilding trust as the customers lead technical partner.
• Data Platform & Architectural Modernization: Partner with client business leaders to evaluate legacy technology estates (e.g. monolithic SQL databases or unmaintained ETL jobs). Lead engineering efforts to refactor legacy data setups into modern lakehouses event-driven streaming systems and scalable vector/graph databases.
• Spec-Driven Development (SDD) for Data & AI: Apply a spec-first engineering workflow using Generative AI tools. Write structured specifications (data models API schemas transformations and evaluation metrics) that instruct AI agents to generate production data models PySpark jobs data pipelines and test suites.
• Agentic AI & LLMOps Implementation: Architect and deploy GenAI workflows Retrieval-Augmented Generation (RAG) pipelines and autonomous AI agents using frameworks such as LangChain LlamaIndex or DSPy. Establish robust evaluation frameworks (Evals) for model accuracy latency and hallucination control.
• Production MLOps & Orchestration: Build deploy and maintain robust ML training and inference pipelines using tools like MLflow Kubeflow Airflow or Dagster. Ensure continuous integration/continuous deployment (CI/CD) for models and data workflows.
• Polyglot Data Engineering: Design and audit production code across data-centric languages and frameworks (Python SQL Scala Go Rust or TypeScript) based on speed concurrency and memory requirements.
• Client Enablement & Knowledge Transfer: Elevate customer teams by establishing reusable agentic development patterns modern MLOps practices data reliability frameworks and SDD methodologies so systems remain maintainable long after deployment.

Requirements

• 10 Years of Experience: Proven track record as a Principal Data Engineer Lead ML Engineer or Enterprise Data Architect building and scaling distributed data and ML platforms.
• Customer-Facing Aptitude: Strong executive presence and communication skills to interface directly with technical teams and business stakeholders under pressure.
• Data & ML Engineering Depth:
  • Data Infrastructure: Mastery of distributed computing (AWS Glue Apache Spark Databricks) modern data warehouses (Redshift Snowflake modeling tools (dbt) and data orchestration (Airflow etc)
  • AI/ML & Vector Architecture: Hands-on experience fine-tuning evaluating and deploying LLMs embedding models and vector stores
  • Polyglot & Framework Proficiency: Advanced proficiency in Python and complex SQL plus fluency in at least two other languages used in modern backend/data systems (e.g. Scala Go Rust TypeScript).
• Generative AI & SDD Experience: Demonstrated skill in using natural language and structured specs to guide AI tools (Claude Code Cursor Copilot) in generating data pipelines schemas and API adapters.
• Cloud & Infrastructure: Hands-on experience with cloud-native data services on AWS or Azure containerization (Docker Kubernetes) and Infrastructure as Code (Terraform).
• Willingness to Travel: Comfort with occasional travel to customer sites as needed.

Preferred Qualifications

• Prior experience in a Forward Deployed Engineer Data Architect or technical consulting/professional services role.
• Experience migrating legacy on-premise data warehouses or legacy Hadoop estates to modern cloud lakehouses.
• Deep understanding of data governance security compliance (HIPAA SOC2 GDPR) and privacy-preserving machine learning.

Compensation & Perks

• Competitive compensation package (160K - 180K CAD / year)
• Retirement Savings Matching Program (RRSP)
• Access to the latest tech
• Partnership with Perkopolis Discounts

Flexibility & Time Off

• Remote first work environment
• Flexible work hours & location
• Paid parental leave options

Health & Wellness

• Employer paid health & dental premiums
• GreenShield Counselling Mental Health
• $500 in Health Care Spending Account annually

Growth & Development

• Peer recognition rewards

As an employer OpsGuru a Carbon60 Company recognizes the importance of balancing our careers with other aspects of our lives and our culture reflects this ethos - from flexible work hours to health and wellness incentives and having fun along the way. We look for people who thrive in an environment of accountability and at times ambiguity as we adapt and grow our business.

OpsGuru is an equal-opportunity employer. We welcome and encourage applications from people with all levels of ability. Accommodations are available on request for candidates taking part in all aspects of the selection process. We thank all applicants for their interest in this exciting opportunity.

Only candidates that meet the qualifications will be contacted for an interview.

Required Experience:

Senior IC