Lead Python Specialist Jobs

FEQ327R400 Mission Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team. The impact you will have: Partner with the sales team to help customers understand how Databricks can help solve their business problems Provide technical leadership for customers to evaluate and adopt Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present references architectures, how-tos, and demo applications for customers Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars Travel to customers in your region What we look for: 7+ years in a customer-facing pre-sales, technical architecture, or consulting role Experience designing and architecting distributed data systems Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R Have built solutions with public cloud providers such as AWS, Azure, or GCP Data Engineering technologies ( Ex: Spark, Hadoop, Kafka )

FEQ427R58 Mission Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team. The impact you will have: Partner with the sales team to help customers understand how Databricks can help solve their business problems Provide technical leadership for customers to evaluate and adopt Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present references architectures, how-tos, and demo applications for customers Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars Travel to customers in your region What we look for: 6+ years in a customer-facing pre-sales, technical architecture, or consulting role Experience designing and architecting distributed data systems Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R Experience supporting Public Sector clients Have built solutions with public cloud providers such as AWS, Azure, or GCP Data Engineering

FEQ227R170 Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks. The impact you will have : Partner with the sales team to help customers understand how Databricks can help solve their business problems Provide technical leadership for customers to evaluate and adopt Databricks Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications Build and present reference architectures, how-tos, and demonstrate applications for customers Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars Travel to meet with customers in your territory What we look for : 7+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges Experience designing and architecting distributed data systems Comfortable programming in, and debugging, at least one of: Pyth

FEQ427R139 Mission Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team. The impact you will have: Partner with the sales team to help customers understand how Databricks can help solve their business problems Provide technical leadership for customers to evaluate and adopt Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present references architectures, how-tos, and demo applications for customers Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars Travel to customers in your region What we look for: 8+ years in a customer-facing pre-sales, technical architecture, or consulting role Experience designing and architecting distributed data systems Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R Experience supporting Public Sector clients Have built solutions with public cloud providers such as AWS, Azure, or GCP Data Engineerin

Leidos is seeking a Principal Network Engineer – Wireless to lead engineering, deployment, and modernization of a large-scale, geographically distributed enterprise wireless network supporting a Department of Defense environment. The engineer will provide technical leadership for Aruba wireless architecture, RF performance, secure network access, integration, troubleshooting, and transition to operations. The environment includes Aruba AOS 10, Aruba Central On-Premises, distributed Aruba ClearPass, Cisco ISE coexistence, certificate-based 802.1X authentication, Comply-to-Connect enforcement, wireless intrusion detection and prevention, and enterprise monitoring. The engineer will collaborate with network, identity, cybersecurity, and operations teams to deliver secure, reliable wireless services at scale. Clearance Requirements Active DoD Secret clearance; ability to obtain additional access if required by the assigned environment. Primary Responsibilities Wireless Architecture and Deployment Design, deploy, configure, and optimize enterprise Aruba wireless infrastructure, including access points, gateways, management platforms, redundancy, and lifecycle upgrades. Engineer and sustain Aruba Central On-Premises and AOS 10 configurations, provisioning workflows, high availability, and enterprise configuration standards. Lead RF design, site surveys, channel and power planning, capacity analysis, roaming optimization, and wireless QoS for voice and mission-critical applications. Network Access Control and Security Integrate Aruba ClearPass and Cisco ISE with 802.1X/EAP-TLS, RADIUS, certificate-based authentication, endpoint profiling, and Comply-to-Connect policies. Engineer wireless security controls, including network segmentation, WPA3, WIDS/WIPS, secure guest access, an

Description Dawn Aerospace is looking for a System Design Engineer to lead the system-level development of custom spacecraft propulsion systems. In this role, you will be responsible for the full development lifecycle, from requirements definition and concept development through detailed design, integration, testing, and delivery. The role involves close collaboration with customers, project managers, and multidisciplinary engineering teams. Key Responsibilities Act as the technical lead for the entire development cycle of a custom propulsion system Define and manage system-level requirements and establish their verification methods Define the technical budgets for the propulsion system Define the propulsion system architecture Develop the detailed design of the propulsion system Support AIT activities during propulsion system integration and testing Serve as the technical point of contact for the customer Work closely with project management and subsystem experts Required Experience: A degree in aerospace, mechanical, or system engineering, or a closely related technical discipline At least three years of experience in the design and development of spacecraft systems or comparable hardware Experience in customer engagement Demonstrated ability to work within multidisciplinary engineering teams Proficiency in computer-aided design; experience with SolidWorks is preferred Experience using MATLAB, Python, or comparable tools for engineering analysis, modelling, data processing, or workflow automation Desired Experience Experience with chemical or electric spacecraft propulsion systems Hands-on experience with aerospace hardware assembly, integration, and testing Working knowledge of ECSS, NASA, or comparable industry standards Experience collaborating across geographically distributed engineering teams Experience delivering flight hardware through rapid development cycles Note that the role is a permanent position that will start with a fixed-term contract of 12 month

Leidos is seeking a Test and Integration Engineer to lead cutting-edge testing and validation efforts within the Undersea Systems Division (USD) . This role is a unique opportunity to drive innovation in testing underwater vehicle systems, maritime sensors, subsea telemetry, and ISR solutions that support critical defense and national security missions. You'll contribute to a multidisciplinary team focused on testing, integrating, and validating advanced maritime technologies, ensuring system reliability and performance from prototype design to full-scale system deployment for ongoing Navy missions. Leidos’ Undersea Systems Division is a recognized leader in C4ISR technologies, delivering innovative, mission-critical solutions across sensor networks, unmanned systems, and tactical platforms . We’re known for achieving “industry firsts” in the most challenging maritime domains. Join us and be part of a world-class team delivering unmatched solutions for today's most pressing maritime missions. Why Join Us? Make an Impact : Your work will directly support U.S. maritime dominance and national security. Lead Innovation : Be at the forefront of applying innovative technology and autonomy to real-world maritime systems. Work with Experts : Collaborate with a top-tier team of engineers, scientists, and technicians located across the U.S. Shape the Future : Influence both the strategic and tactical direction of next-generation subsea technologies. What You’ll Do Test and Validate: Write, develop and execute comprehensive test plans, procedures, and protocols to ensure system functionality, reliability, and compliance with requirements. Integrate systems and conduct hands-on testing: Write, develop, and execute integration plans to bring complex systems together. Perform field</b

About the Job: We are seeking an Engineering Manager to lead LaunchDarkly’s Data Platform team and help shape the high-throughput data backbone behind our most important products. As Engineering Manager, you’ll lead a technically deep team building and operating the systems that ingest, process, and serve the real-time and batch data powering Experimentation, Metrics, Observability, Release Guardian, AgentControl, and Data Export. Working primarily in Go and Python, your team tackles ambitious distributed-systems challenges with technologies including Kinesis, Airflow, Athena, and Iceberg on S3, ClickHouse, Elasticsearch, Terraform, AWS, and Datadog. From evolving real-time analytics and context data to strengthening streaming and batch pipelines, you’ll guide the platform that turns vast volumes of events into reliable, customer-facing product experiences while partnering across Core Engineering and product teams to make data faster, more resilient, and more useful for every LaunchDarkly customer. Responsibilities: Lead and develop a team of backend engineers, providing coaching, feedback, and career growth opportunities Own the delivery, correctness, and resilience of Data Platform's production systems, including Tier 0 ingestion endpoints and the pipelines and data stores behind them Partner with Product Management and consuming engineering teams to scope, estimate, and sequence roadmap work, making tradeoffs in real time Act as the primary communicator and point of contact for Data Platform with engineering leadership, partner teams, and customers Drive operational excellence: reliability, observability, cost, incident response, and on-call health Build team working norms that promote collaboration, reduce silos and bus factor, and keep engineers engaged Participate in hiring to grow the team and raise the engineering bar Qualifications: 8+ years of experience in software engineering, with at least 2 years managing a team of backend or infrastructure engineers E

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We're looking for a Staff Software Engineer to lead the technical direction of the backend systems powering Pinterest's AI-driven product experiences — Pinterest Assistant, visual editing and content creation tools and future LLM-based products. You'll design and ship backend systems while architecting the broader platform strategy that enables these experiences to scale across surfaces and teams. This is a hands-on leadership role where you'll move between deep technical execution, system-level architecture and cross-team technical leadership. What you'll do: Define the backend and platform architecture for AI-driven product experiences — visual-chat, AI image generation and editing, and agentic or LLM-based products — partnering with Engineering, Product, ML and UX leaders to shape the technical vision and roadmap. Architect end-to-end systems

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

Perplexity is seeking a TLM (Tech Lead Manager) to lead and grow our highly driven Agents engineering team. The Agents team consists of AI/ML, backend, and full-stack engineers who collaborate to build delightful agentic experiences within our Comet ecosystem . Our vision is to empower our users with AI agents that can faithfully actualize their intent, however and wherever expressed, through open-ended interactions with the world. As the Agents TLM, you will bring AI expertise, sharp product intuition, and strong engineering management skills to advance the frontier of what agents can accomplish for our millions of devoted users. You will lead, grow, and support a team in solving many open problems in AI, including: Designing AI agents to navigate the digital world and perform increasingly valuable units of work for our users; Training action and decision models that determine, based on complex multimodal states, how to accomplish user-specified objectives; Providing consistently excellent experiences across desktop, mobile, headless cloud, and other environments through flexible abstractions and frictionless backgrounding; Developing permission architectures, payload classifiers, and other methods to implement secure-by-design agentic capabilities; Designing optimal data representations and modes of interaction between agents and their environments; and much, much more. Responsibilities Provide technical leadership across multiple layers of a rapidly growing product in the AI agents space. Develop and leverage cutting-edge AI models, infrastructure, and browser technologies to advance the capability frontier and scale those capabilities for a rapidly growing userbase. Exercise sharp technical & product intuition to guide the team’s system architectures and product roadmaps. Drive product reliability, code quality, AI evaluation, testing, and maintenance for the broader team. Oversee hiring, onboarding, and mentorship for a rapidly growing team. Develop rigorou

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, AI INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, AI INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from