The team focuses on
Developing intelligent, AI-driven applications powered by large language models
Integrating generative AI capabilities into enterprise platforms and workflows
Building scalable systems that combine AI, data, and distributed architectures
Enabling automation, developer productivity, and intelligent decision-making
While these capabilities rely on strong data foundations, the primary focus is on applying AI and generative AI to solve real-world business problems at scale, with enterprise-grade security and reliability.
Job Summary
Staff Data Engineers are expert problem-solvers, builders, and technical leaders who design and evolve platforms powering next-generation AI and data-driven applications. In this role, you will work extensively hands-on with code, data, and modern technologies to deliver secure, scalable, and high-performance systems that drive business outcomes.
You will play a key role in developing GenAI-powered applications and platforms, including integrating with leading large language models such as OpenAI and Anthropic, and enabling their safe, scalable, and efficient use in enterprise environments.
You will independently understand data ecosystems, system design patterns, and security, privacy, and governance requirements, applying this knowledge to design robust and production-ready solutions. You will translate complex business requirements into scalable architectures and guide implementation across the team.
This role requires strong expertise across backend engineering, data platforms, microservices, and real-time distributed systems, along with the ability to influence engineering practices and drive high standards across teams.
All roles require digital fluency, including hands-on experience or familiarity with Generative AI tools (e.g., Claude Code, Cline, Codex, and GitHub Copilot) to enhance developer productivity and enable intelligent engineering workflows.
Key Responsibilities
Act as a key technical contributor in stakeholder discussions to clarify requirements and drive architecture and design decisions
Design and deliver scalable, resilient platforms and services supporting AI/GenAI applications and data-driven systems
Translate functional requirements into end-to-end system architectures, leveraging established design patterns
Build and integrate applications with large language model providers such as OpenAI and Anthropic
Design and implement GenAI workflows, including prompt orchestration, context handling, and system integration layers
Lead development of microservices, APIs, and platform components supporting distributed systems
Build and optimize real-time data streaming and event-driven architectures for high-throughput applications
Implement extensible, maintainable, and reusable code following best practices, security standards, and coding guidelines
Take end-to-end ownership of data products, platform components, or services, including reliability, scalability, and maintainability
Drive code reviews, mentor engineers, and guide teams on system design, coding practices, and performance optimization
Build tools and automation to improve data processing, deployment, monitoring, and platform operations
Ensure adherence to data management principles, governance, security, and compliance requirements
Identify and address technical debt, and continuously improve system design and performance
Lead troubleshooting of complex issues across distributed systems and drive root cause resolution
Support platform upgrades, scaling initiatives, and security remediation activities
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications
5+ years of relevant work experience with a Bachelor's degree, or 2+ years with an advanced degree, or 8+ years of relevant work experience
Strong core programming skills in Java, Python, or similar languages, with ability to write scalable, maintainable, and high-quality code
Experience designing and implementing data pipelines, distributed systems, and large-scale data processing jobs
Experience building and operating microservices-based architectures and APIs
Experience working with real-time data streaming or event-driven systems
Experience developing unit, integration, and end-to-end tests with a strong focus on automation
Experience building and maintaining CI/CD pipelines and deploying applications using containerization and orchestration tools
Experience working with cloud platforms such as AWS, including building and operating scalable, cloud-native applications
Experience monitoring applications in production and troubleshooting issues using observability and logging tools
Experience integrating AI/ML or Generative AI services into applications, including working with LLM-based systems
Experience collecting and analyzing metrics to drive system optimization, performance, and reliability improvements
Experience collaborating with cross-functional stakeholders to clarify requirements and deliver robust technical solutions
Experience applying secure coding practices and complying with enterprise security and regulatory standards
Preferred Qualifications
6+ years of work experience with a Bachelor’s degree or 4+ years with an advanced degree
Hands-on experience building applications using LLM providers such as OpenAI, Anthropic, or similar platforms
Experience designing and implementing GenAI workflows, including prompt design, context management, and orchestration patterns
Experience with data and distributed technologies (Kafka)
Experience building and operating high-throughput, low-latency real-time systems
Experience working with advanced AWS services for large-scale systems
Strong experience in building, deploying, and operating production-grade systems at scale
Experience mentoring engineers and driving engineering best practices across teams
Ability to write clear, concise technical documentation and architecture designs
Experience staying current with emerging trends in AI, GenAI, cloud platforms, and distributed systems, and applying them to real-world problems
AI Engineering
Familiarity with concepts such as
Prompt engineering
System prompts and instruction design
Retrieval-augmented generation
Vector search
Embeddings
Tool calling
Function orchestration
Context management
Agent memory
Evaluation datasets
Model benchmarking
Feedback loops
A2A and MCP Protocols
Experience with agentic AI frameworks or tools such as
LangChain
LangGraph
Model Context Protocol Servers
Spring AI
OpenAI and Anthropic SDKs
Vector databases
Knowledge graphs
Model evaluation frameworks
Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost.
Experience using commercial or open-source AI models and APIs.
Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement.
Software Engineering
Strong programming ability in one or more languages such as
Python
TypeScript / Node.js
Go
Java
Experience building backend services, APIs, data pipelines, integrations, or cloud-native applications.
Familiarity with web applications, distributed systems, databases, CI/CD pipelines, logging, monitoring, and automated testing.
Ability to write clean, maintainable, secure, and production-ready code.
Experience participating in design reviews, code reviews, and production troubleshooting.
Visa is an EEO Employer
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
