Top Tech Jobs & Startup Jobs

Designs and operates scalable multi-cloud data platforms, real-time and batch pipelines, lakehouse architectures, and distributed processing systems. The role focuses on Kafka, Spark, BigQuery, Airflow, Terraform, Kubernetes, data reliability, governance, security, and warehouse performance. It also leads technical architecture reviews, mentors engineers, and drives engineering best practices.

Own and improve a production Voice AI and LLM application for a regulated insurance organization. Build agentic workflows using prompts, tool calling, structured outputs, and RAG; work with Amazon Connect, Lex V2, and Bedrock; create evaluation suites and quality gates; improve latency, reliability, security, governance, and cost; and implement PII/PHI safeguards for production releases.

Support an ERP migration from Quantum Control to VistaSuite by reviewing and optimizing Oracle SQL/PLSQL extraction scripts, validating CSV and ERP outputs, identifying mapping and completeness issues, investigating source-to-target discrepancies, and reconciling loaded data across purchasing, inventory, production, logistics, repair, and disassembly.

Lead and mentor engineering teams while owning engineering strategy, architecture, scalability, reliability, security, and delivery. Partner with Product, Business, Data, and Technology stakeholders on priorities and trade-offs. Support cloud infrastructure, platform performance, cost optimization, AI adoption, and continuous improvement. The role requires strong system design knowledge, executive communication, and experience in fast-paced product-led or regulated environments.

Lead backend development using Python, Django, and FastAPI to build scalable applications and high-performance REST APIs. Responsibilities include system architecture, clean code development, code reviews, technical discussions, cross-functional collaboration, and mentoring junior developers. The role requires database experience with PostgreSQL, MySQL, MongoDB, and Redis, along with expertise in scalable architecture and backend engineering best practices.

Translates business needs into functional and technical requirements for software delivery. Responsibilities include gathering requirements, creating user stories and process flows, defining system behavior and integrations, analyzing process gaps, supporting QA and user acceptance testing, managing requirement changes, assessing impacts, and maintaining traceability. Collaborates with clients, product teams, engineers, QA teams, and stakeholders throughout Agile software development projects.

Build and maintain Java backend services and APIs for a card issuance platform. Responsibilities include card lifecycle, transactions, settlement, reconciliation, processor and partner integrations, event-driven systems, testing, auditability, operational visibility, code reviews, releases, troubleshooting, and collaboration with product and engineering teams.

Design and maintain API, web, or mobile automation frameworks using Java, Rest Assured, Playwright, and TypeScript. Develop functional, integration, regression, and end-to-end tests; conduct performance testing with K6; validate APIs, databases, and distributed workflows; integrate tests into CI/CD pipelines; manage test execution and defects; debug failures; and collaborate with engineering and product teams to improve quality throughout development and production.

Own the roadmap and development of fraud prevention, detection, and Trust & Safety products. Define requirements, fraud signals, risk scores, alerts, decisioning, and success metrics for real-time transaction monitoring. Partner with Engineering, Data Science, Risk, Compliance, Operations, and Analytics teams to address account takeover, SIM swap, identity, and payment fraud. Analyze fraud trends, false positives, customer friction, and performance metrics to continuously improve controls and balance security with customer experience.

Build and deploy production-grade AI agents, intelligent workflows, automations, and integrations. Develop memory, context, retrieval, prompt, tool, guardrail, evaluation, testing, and observability frameworks. Create secure Python and FastAPI APIs and integrate AI systems with event streams, vector databases, and enterprise platforms. Collaborate with product, engineering, and business stakeholders to turn ambiguous problems into reliable AI products.