• Work directly with clients to identify their highest-impact problems • Translate client problems into structured approaches • Design and deploy scalable, AI-powered solutions • Operate side-by-side with clients building in real time • Iterate quickly and demonstrate value throughout the engagement • Define, solve, and ensure solutions are adopted in high-stakes environments

Role Description Workato Inc. seeks Staff Engineer in Palo Alto, CA. - Design and develop production-grade distributed services in Rust using async/Tokio, focusing on concurrency, performance, and scalability. - Own the full service lifecycle from system design and implementation through deployment and operations. - Build and optimize data-processing and transformation pipelines with emphasis on throughput, latency, and memory efficiency. - Create and maintain integration tests with real service dependencies in containerized environments. - Improve test determinism, stability, and reliability across distributed systems. - Deploy and operate services across development, staging, and production environments using infrastructure-as-code practices. - Implement safe rollout and rollback procedures using GitOps and CI/CD workflows. - Develop and evolve observability systems including logs, metrics, and distributed tracing. - Define service-level objectives (SLOs), configure alerts, and lead incident response and post-incident reviews. - Design and maintain distributed cluster coordination systems using gossip-based membership and leader-election mechanisms for resilience and scalability. - Plan and execute performance benchmarking and load testing, including capacity modeling and regression detection. - Drive performance optimization initiatives across distributed services. - Apply fuzz testing techniques to critical components to improve reliability and security. - Practice chaos engineering in lower environments through fault injection, network partitioning, and resource pressure testing to validate resilience and recovery objectives. - Participate in architecture reviews and code reviews. - Contribute to technical design documents and RFCs. - Mentor peers and collaborate cross-functionally on service integrations and stateful components. - Full-time telecommuting permitted from anywhere in the United States. Qualifications - Bachelor’s degree (or foreign equivalent) in Computer Science, Management, or a closely related field. - 5 years of progressively responsible experience in the job offered or a related occupation. Requirements - 3 years of experience with Rust, including Tokio, asynchronous programming, concurrency, performance optimization, and allocator profiling. - 2 years of experience with Apache DataFusion and Apache Arrow, including Parquet, data pipelines, query planning, and vectorized execution. - 3 years of experience creating integration tests with real dependencies using Docker and Testcontainers. - 2 years of experience with behavior-driven testing for distributed services using frameworks such as Gherkin and Cucumber. - 2 years of experience with performance benchmarking, including throughput and latency analysis, regression detection, and capacity planning. - 2 years of experience with load testing using Locust and wrk, including test scenario design, ramp-up strategies, and analysis of latency, throughput, and error rates. - 1 year of experience with chaos engineering and fault injection, including network partitions, process termination, and resource pressure testing for resilience validation. - 2 years of experience designing and scaling distributed backend services, including rate limiting, fair queuing, back-pressure control, cluster coordination, gossip-based membership protocols, and leader election. - 3 years of experience with Kubernetes for production deployments, rollouts, and rollbacks across multiple environments. - 3 years of experience with Terraform and infrastructure-as-code practices for service provisioning and configuration. - 3 years of experience with advanced Redis patterns, including counters, streams/pub-sub, distributed locks, and idempotency controls. - 2 years of experience with PostgreSQL, including SQL optimization, JSON/JSONB, indexing, and locking, as well as columnar OLAP databases such as ClickHouse. - 2 years of experience with Ruby for backend and service tooling, including fuzz testing and library development. - 2 years of experience with Java or Kotlin for backend services. - 3 years of experience implementing observability and CI/CD systems, including Prometheus, OpenTelemetry, GitHub Actions, and ArgoCD. - 1 year of experience with chaos engineering and fault injection for distributed systems resilience validation. Benefits - Salary: $264,514.00-285,000.00 per annum. - 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m. - Must be legally authorized to work in the U.S. without sponsorship.

Role Description We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. - Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. - Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. - Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. - Solve edge-case scenarios by designing and refining manual prompts. - Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. - Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. - Draft technical launch readiness justifications (Launch Certification Documentation) for final. Qualifications - Native fluency in English. - Must be based in the United States. - Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. - At least 4 years' experience as Prompt Engineer. - Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. - Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. - Ability to quickly learn and master proprietary tools with minimal supervision. - Excellent verbal and written communication skills. Requirements - Familiarity with enterprise-grade LLM interfaces like the Goose API. - Experience in AI model evaluation, data science, computational linguistics, or software engineering. - Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. - Linguistic expertise, including an understanding of semantics and logic. Federal Law Compliance - In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States. - Complete a required employment eligibility verification form. - All new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment. To know more details (Click here) We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

• Conduct deep technical discovery in selected strategic accounts to assess platform readiness, evaluate constraints, and identify high-value adoption opportunities across GitLab and GitLab Duo Agent Platform. • Lead architecture and delivery design for complex enterprise environments where platform migration, regulated requirements, and product boundaries intersect. • Partner with customer stakeholders and GitLab account teams to prioritize use cases based on business impact, technical feasibility, repeatability, and long-term platform value. • Design and build bounded proofs, prototypes, deployment patterns, and reusable accelerators across source code management, CI/CD, security, compliance, and AI-enabled workflows. • Architect self-managed and enterprise deployments, including runners, access controls, network boundaries, observability, AI Gateway, model connectivity, and governance controls. • Turn recurring field patterns into reusable assets such as runbooks, templates, design notes, technical guidance, product briefs, and reference architectures that can be used across accounts. • Contribute code, technical designs, or architecture changes when strategically necessary, in partnership with product and engineering, to address blockers that should be solved upstream. • Travel as needed for strategic customer engagements, architecture workshops, and team coordination, with expected travel up to 50%.