Top Tech Jobs & Startup Jobs in Boston, MA

Design, build, and maintain cloud-native ETL/data pipelines using Databricks and AWS Glue. Ingest and transform structured and semi-structured data with PySpark, Python, and SQL. Integrate sources including MongoDB, implement data quality checks, optimize pipeline performance, and support production deployments, monitoring, and troubleshooting while collaborating with architects and analysts.

Build and maintain backend systems across multiple languages and stacks, contribute to Generative AI projects (RAG/LLMs), collaborate with cross-functional teams, write clean maintainable code, participate in code reviews, and troubleshoot complex multi-stack issues.

Lead architecture and delivery of AI-first, agentic systems: design LLM integrations, RAG pipelines, multi-agent workflows, Python-based scalable backends, distributed event-driven microservices, and cloud-native solutions; ensure performance, security, cost optimization, and provide technical leadership across engineering and product teams.

Build and maintain scalable backend services in Python and Java (Spring Boot), develop responsive React frontends, integrate AI/GenAI (LLMs, RAG) using frameworks like LangChain/LlamaIndex, collaborate with cross-functional teams, troubleshoot and optimize systems, and ensure coding, security, and performance best practices.

Technical authority responsible for shaping system architecture, architecting and scaling distributed cloud-native platforms, leading technical decisions and reviews, mentoring engineers, and applying AI/GenAI to business problems.

Design, build, and operate large-scale batch and streaming ingestion pipelines, medallion/lakehouse layering, identity resolution and golden-record consolidation, data-quality gates and reconciliation, source-to-canonical mappings and crosswalks, schema enforcement, and observability for client onboarding and production data flows.

Lead a team of developers to design, architect, and deliver scalable, secure microservices-based enterprise applications. Hands-on coding, code reviews, performance tuning, CI/CD, cloud deployments, stakeholder collaboration, and mentoring. Drive architecture, HLD/LLD, root-cause analysis, and timely delivery in Agile environments.