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Leads a data science team at LexisNexis building AI-powered legal drafting and retrieval tools, combining people management with hands-on technical direction over LLMs, RAG pipelines, embeddings, reranking, and evaluation. Core stack includes Python, LangChain, vector databases, and cloud ML infrastructure.
Builds and enhances Verily Workbench, a secure multi-cloud collaboration platform that lets research and biopharma organizations govern and analyze health data for precision health. Day-to-day involves designing and shipping features using Google Cloud, Go, Java, React, Terraform, and Kubernetes.
Founding, hands-on Information Security Lead at Acquisition.com who owns GRC and security operations: running ISO 27001/42001 management systems, building logging/detection/incident response, and reviewing application code, IAM, and infrastructure-as-code for risk. Core tech includes Python/TypeScript, Terraform/Pulumi, cloud IAM, CI/CD, and security controls for AI/agentic systems.
KLA's IT group in Ann Arbor is hiring a Graduate AI Engineer Intern to build AI-enabled enterprise systems: training and deploying ML models, designing RAG architectures, and building APIs, microservices, AI agents, and copilots. Open to currently enrolled graduate students or PhDs in CS or related fields.
Graduate intern on KLA's IT team in Ann Arbor building AI-enabled enterprise applications: conversational AI with LLMs, AI agents and multi-agent workflows, ML model training/deployment, and APIs/microservices exposing AI capabilities, using Python/Java/C-family languages and web frameworks.
An intern in KLA's e-Beam division (Milpitas, CA) researches and prototypes cutting-edge image-processing and machine/deep-learning algorithms for next-generation semiconductor defect-inspection products, including generative/diffusion models for SEM image simulation and image quality enhancement. Core tools: Python, TensorFlow/PyTorch, MATLAB.
Platform Engineer on the Veeam Data Cloud team, building and automating the internal developer platform and public cloud infrastructure that powers Veeam's SaaS data protection product. Day to day: writing automation code (Go, Bash, TypeScript/Python), managing Kubernetes on Azure/AWS with Terraform and Helm, plus on-call rotation.
Designs strategic, cross-functional AI solutions for Veeam's internal Corporate Technology team: defines scope and requirements with business leaders, architects scalable solutions on AWS using distributed-systems and integration patterns, and drives rollout, documentation, and adoption. Works with AI platforms, Python/Go/TypeScript, UML, and ITIL/ITSM/Agile practices.
Staff Software Engineer on the Veeam Data Cloud team, building greenfield, highly reliable SaaS microservices for data protection in Golang on Azure/AWS/GCP with Docker/Kubernetes and event-driven architectures. Also drives technical vision, leads cross-team deliverables, reviews code, and joins an on-call rotation.
Founding-level Security Engineer at AfterQuery, building the company's entire security posture from scratch — cloud/production security on GCP/AWS, scalable incident detection and response, and securing sensitive AI training-data flows — while contributing to core infrastructure in Python, Go, and TypeScript. On-site in San Francisco, 5 days a week.
Lead QA Engineer at Qualys in Pune owning end-to-end quality for its cybersecurity and compliance SaaS products: defining test strategy, mentoring QA engineers, and hands-on building of automation across React/TypeScript UIs, Java/Spring Boot microservices, REST APIs, and Kafka pipelines, with a focus on AI-driven self-healing automation and LLM-assisted QA.
Senior engineer at Westwing in Munich designing and evolving the order management and commerce platform built on Fluent Commerce. Day to day: building Fluent workflows, Java-based rules via the Rules SDK, and GraphQL/REST/event-driven integrations, owning order-management flows end-to-end from architecture to production monitoring.
Palantir is hiring a Deployment Strategist for its US Government work in Laurel, MD. The role embeds with government customers to understand their workflows, identify and integrate datasets, build bespoke analytics workflows, train users, and present results. Requires an active Top Secret (or higher) clearance and 25–75% travel; Python/R/SQL experience is a plus.
Designs and deploys end-to-end data solutions for US Government customers on Palantir's platforms — from system design and prototyping to application development and data integration — iterating directly with customers on-site. Stack includes Java, Python, TypeScript/React, Postgres/Cassandra/Hadoop/Spark, and AWS; requires an active Top Secret clearance.
Firewall/network security engineer supporting a large Federal agency: configuring FortiGate firewalls, IPsec/SSL VPNs, FortiManager and FortiAnalyzer, plus security controls per NIST 800-53. Core stack is the Fortinet ecosystem, general networking, and Python-based automation.
Owns end-to-end delivery of Distyl's AI platform into Distyl-hosted, customer VPC, and on-premises environments: designing portable cloud architectures, deploying via IaC/Docker/Kubernetes, and building reusable provisioning automation in Python or Go across AWS, Azure, and GCP. Customer-facing, hybrid in San Francisco (3+ days/week).
Infrastructure engineer owning how Distyl's engineers build, test, secure, and release software across multi-cloud customer deployments. Day to day: build/release pipelines, reproducible builds, supply-chain security (signing, SBOMs), and coding-agent tooling using Python, Linux, Kubernetes, GitOps, IaC, and AWS/Azure/GCP.
Hands-on Platform Engineer (DevOps/Infrastructure) at FairPlay Sports Media, owning GCP infrastructure, Terraform, GKE/Kubernetes workloads, GitLab CI/CD, and observability for a high-traffic AI/data-powered sports media and betting platform. Hybrid from London Waterloo (~monthly office travel) with a week-in-six on-call rota.
Staff engineer serving as technical lead for PayPal's API Management platform: designing, building, and operating core APIM components (governance, lifecycle, security, observability), setting technical direction, mentoring engineers, and owning platform availability with on-call. Built with Java/Python, REST/GraphQL/gRPC APIs, gateways, OAuth2, cloud (GCP/AWS), Terraform, Redis, and Kafka.
Data Engineer on the Business Intelligence team at an iGaming company, building and maintaining batch and streaming data pipelines on a cloud stack — Kafka, Spark on AWS EMR, S3, Snowflake, dbt and Airflow — while monitoring data quality, performance and scalability.
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