Top Tech Jobs & Startup Jobs in Boston, MA

Provide timely technical support through phone, email, and chat; diagnose hardware, software, and network issues; guide users through solutions; escalate unresolved problems; and document requests and resolutions in a ticketing system.

Build retrieval-augmented generation systems and engineer AI context using Azure AI Search and Cosmos DB vector search. Integrate a parts agent with an existing manuals agent and develop hands-on generative AI platform capabilities.

Leads end-to-end technology delivery for fraud-related client projects and initiatives. Coordinates internal teams, service providers, vendors, stakeholders, and engineering groups; manages risks, issues, metrics, integrations, and system enhancements. Guides technical trade-off decisions while balancing business objectives, platform strategy, customer experience, and maintainability. Analyzes complex application-support problems, recommends solutions, and provides technical oversight across the fraud book of work.

Lead full-stack development using Java, Angular, and AWS cloud services. Build distributed, cloud-native applications and microservices with Spring, Spring Boot, Hibernate, REST, and SOAP integrations. Develop AWS serverless and containerized solutions using Lambda, API Gateway, SQS, SNS, Step Functions, CloudFormation, and CI/CD services. Work in Agile Scrum environments and support application integrations involving ESB, JMS, and file or data transfers.

Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.

Leads end-to-end technology delivery for fraud-related client projects and initiatives. Coordinates internal teams, vendors, product owners, analysts, and engineering groups; manages requirements, risks, issues, integrations, system enhancements, and support impacts. Evaluates complex business processes and application logic, recommends solutions, establishes success metrics, and guides stakeholders through technical and business trade-offs.

Leads end-to-end technology delivery for fraud-related projects and initiatives. Coordinates internal teams, vendors, and service providers; manages risks, issues, requirements, system impacts, and application enhancements. Partners with product owners, business analysts, systems analysts, engineering teams, and management to align integrations, support requirements, business objectives, customer experience, and technical strategy. Analyzes complex application problems and recommends practical solutions.

Design, develop, and maintain enterprise AI applications, including conversational assistants, copilots, autonomous agents, RAG solutions, and workflow automation. Build scalable APIs and microservices integrating foundation models and enterprise systems. Apply prompt and context engineering, memory management, observability, governance, and performance optimization. Collaborate with cross-functional teams to identify automation opportunities and participate in Agile development, code reviews, CI/CD, and DevSecOps.

Lead enterprise Salesforce architecture, development, integration, governance, and delivery. Design scalable solutions across Sales Cloud, Experience Cloud, customer portals, quote-to-cash, contracts, and customer lifecycle processes. Develop Apex, Lightning Web Components, Flows, integrations, reports, and dashboards. Partner with executives and business stakeholders, lead workshops, mentor Salesforce teams, oversee Agile delivery, manage releases and support, and establish technical standards and best practices.

Lead quality assurance for mobile applications across iOS and Android. Develop and maintain test plans, cases, scripts, and automation frameworks; perform functional, regression, integration, usability, and performance testing; validate applications across devices and operating systems; track defects; and collaborate with developers, product managers, designers, and AI teams. Test AI-driven features including chatbots, recommendation engines, and NLP-based search.