Design and build complex agentic systems using LLMs, including RAG pipelines, prompt engineering, evaluation frameworks, and inference endpoints Develop and maintain backend services supporting ML workloads - data ingestion, model evaluation, and production inference Design and maintain cloud infrastructure (Kubernetes, Terraform) to support AI workloads and application deployments Write well-tested, production-ready code with attention to reliability, performance, and developer experience Support the data engineering team with scalable infrastructure for ELT pipelines and data warehousing Contribute to observability, monitoring dashboards, and tooling for ML systems Collaborate with cross-functional teams to translate business requirements into technical solutions and strategies Participate in design reviews, code reviews, and establish engineering best practices via ADRs and knowledge sharing Communicate and present technical solutions, strategy, and roadmaps to ESCI stakeholders and leadership7+ years of software engineering experience, with expertise in backend technologies and AI/ML systems Bachelors in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent industry experience) Proven experience building complex agentic systems using LLMs Strong programming skills in Python; proficiency with backend API service development Hands-on experience with Kubernetes and Infrastructure as Code (Terraform) Familiarity with ML concepts including model inference, evaluation, data pipelines, and LLM application development Experience with a cloud data warehouse - Snowflake preferred (warehouses/roles, performance tuning, cost management) Experience developing ELT pipelines and orchestrating transformations (dbt Cloud, Airflow, Dagster, or similar) Strong proficiency in database technologies and CI/CD solutions Excellent communication skills and ability to collaborate with both technical and non-technical teams Experience leading technical projects and mentoring engineers via PR review, collaboration, and ADRsExperience with RAG architectures, prompt engineering, evaluation pipelines, and agentic workflows Familiarity with ML frameworks such as PyTorch, Hugging Face, or LangChain Experience working on platform engineering or developer experience platforms Experience with data engineering practices including dbt, Snowflake, Databricks, and building data marts for analytics Proficiency in JavaScript/TypeScript for tooling and web application development Experience with CQRS/ES architecture patterns Knowledge of observability tools and practices (Telemetry, Prometheus, Grafana) Experience with GitOps workflows and deployment automation Collaborative mindset with keen interest in keeping up with the latest in the industry Ability to work independently on scoped features with minimal supervision. This role requires excellent communication skills - youll collaborate with ESCI subject matter experts from a variety of disciplines to craft requirements, strategy, and architectural patterns that deliver high-impact solutions.