As a part of a new team focused on accelerating AI adoption and usage, the AI Engineer will design and deploy AI-powered automation, and intelligent agents embedded directly into business operations. This role operationalizes generative AI using governed enterprise data, leveraging enterprise data as the data foundation, and enterprise tools for orchestration and execution.
The position partners with Data, IT, and business teams to automate workflows, support decision-making, and improve operational efficiency. The focus is on applying AI to real processes — not research or model training.
AI & Copilot Development
- Build internal AI assistants and copilots for support, operations, and business teams
- Implement Retrieval Augmented Generation (RAG) using Snowflake data and curated metrics
- Ground AI responses using modeled enterprise data rather than documents alone
- Implement prompt strategies, guardrails, and response evaluation techniques
Workflow & Decision Automation
- Automate operational processes such as ticket triage, routing, approvals, and document handling
- Develop AI-driven classification, summarization, and recommendation services
- Implement human-in-the-loop workflows and exception handling
- Continuously improve workflows based on business outcomes and user feedback
Production Engineering & Integration
- Build and maintain AI-powered backend services, APIs, and microservices
- Integrate AI capabilities with enterprise systems (ITSM, CRM, ERP, and internal applications)
- Troubleshoot failures across data pipelines, orchestration, and model inference layers
- Participate in technical design and architecture discussions
Data Platform Integration
- Utilize Snowflake as the trusted data source for AI decisions
- Use dbt models as the semantic and business logic context for automation
- Enable real-time and batch data-driven decision support
- Ensure AI actions align with defined business metrics and data definitions
Cloud Orchestration & Observability
- Implement serverless workflows using AWS (Lambda, Step Functions, API Gateway, S3, EventBridge)
- Monitor system performance, latency, and operational reliability
- Track AI usage, accuracy, and cost efficiency
- Implement logging, auditing, and traceability of AI decisions
- 5+ years of software or ML engineering experience, with 2+ years of building LLM systems in production.
- Expert-level proficiency in Python, plus TypeScript or Go for full-stack AI applications.
- Proven ability to communicate complex AI concepts clearly to non-technical stakeholders — translating engineering trade-offs and model behavior into business terms that inform decisions.
- Experience implementing production RAG systems using Snowflake Cortex Search, pgvector, hybrid search, and re-ranking strategies.
- Hands-on experience building MCP (Model Context Protocol) servers and clients.
- Proven track record implementing AI observability.
- Experience working with LLM APIs (OpenAI, Anthropic, Azure , Gemini) and cloud platforms (AWS SageMaker, Lambda, S3, Bedrock).
- Familiarity with CI/CD and MLOps tooling (MLflow, Weights & Biases, Snowflake ML Registry).
- Demonstrated application of responsible AI practices on live deployments, including bias checks, output validation, and human-in-loop escalation.
- A track record of proactively evaluating and introducing new AI tools or frameworks that deliver tangible improvement — not just awareness of trends but applied adoption.
- Experience managing production incidents and model rollbacks in high-stakes environments.
- Snowpark or external functions in Snowflake
- Experience with enterprise SaaS platforms (ServiceNow, Salesforce, or similar)
- Workflow orchestration tools (Airflow, n8n, or similar)
- Authentication and access control concepts (OAuth, RBAC, SSO)
- Exposure to vector search or semantic retrieval technologies
This is a remote eligible position. Candidates who live within a 45 mile radius of Boston, MA; Detroit, MI; and Denver, CO will be required to work hybrid (2 days per week) out of our Dyntrace office. Candidates are required to work EST hours for this position.
- Dynatrace is a leader in unified observability and security.
- We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance.
- Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances.
- You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically.
- Over 50% of the Fortune 100 companies are current customers of Dynatrace.
DOE, salary $160K - $180K, plus Health, Dental, Life, STD, LTD, 401K, PTO. Total compensation may vary depending on candidate experience/education and location.
Equal Employment OpportunityAll your information will be kept confidential according to EEO guidelines.
We offer competitive compensation, company-sponsored premium benefits, medical, dental, vacation/holidays, company matching 401(k) Plan, etc. Dynatrace is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, sex, color, gender identity, religion, national origin, ancestry, citizenship, physical abilities, age, sexual orientation, creed, disability status, veteran status, pregnancy, genetic status, or any other characteristic protected by law. If your disability makes it difficult for you to use this site, please contact [email protected]. Dynatrace participates in E-Verify, participant information in English and Spanish. Right to work information in English and Spanish. EEO is the Law. To be considered for this position, please upload your resume/CV.
