Staff Software Engineer, Frontier Security Team
Primary stack
Nice to have's
Job description
About the Position
Staff Software Engineer, Frontier Security Team
IN-Bangalore-MSO
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 Staff Software Engineer for our Frontier Security AI team. Snowflake's Frontier Security AI teams develop production-grade LLM applications, intelligent agents, AI infrastructure, and evaluation systems for enterprise customers - products that must meet a high bar for quality, security, reliability, and efficiency while operating over sensitive data at large scale. In this role, you will lead the design and development of our Agentic Harness and agent evaluation platform, working across product, infrastructure, applied AI, security, and modeling teams to take new capabilities from prototype to dependable customer value.
Responsibilities
- Architect and build the Agentic Harness that executes complex, multi-step AI workflows across models, tools, data, and services.
- Design stable interfaces for tool execution, context construction, state management, memory, permissions, retries, fallbacks, and human review.
- Own agent quality end to end by building evaluation harnesses, representative datasets, automated graders, experiment pipelines, and release gates.
- Convert ambiguous reports such as "the agent feels worse" into measurable failure modes, reproducible tests, and durable fixes.
- Analyze production agent trajectories to identify failures in reasoning, retrieval, tool use, context, orchestration, and application code.
- Close the loop between production incidents, root-cause analysis, evaluation coverage, and regression prevention.
- Develop offline and online measurements for task completion, correctness, groundedness, safety, latency, reliability, and cost.
- Build simulation and replay infrastructure for golden-set tests, adversarial scenarios, model comparisons, and large-scale experiments.
- Improve agent efficiency through model routing, prompt and semantic caching, context compaction, tool-result management, and token optimization.
- Productionize new model capabilities as secure, observable, multi-tenant services with clear operational controls.
- Establish standards for evaluation design, including sampling, ground-truth quality, grader calibration, leakage prevention, and statistical significance.
- Define technical direction across multiple teams and lead projects whose scope extends beyond a single service.
- Mentor engineers, raise the quality of architecture reviews, and remain directly involved in implementation and debugging.
Requirements
- 9+ years of software engineering experience, including technical leadership of complex production systems.
- Direct experience shipping and operating LLM applications, AI agents, or model-backed workflows in production.
- Strong background in distributed systems, service architecture, high-throughput APIs, concurrency, and failure handling.
- Experience building an agent runtime, workflow engine, developer platform, evaluation system, or similar infrastructure.
- Demonstrated ability to evaluate nondeterministic systems without relying on a single aggregate score.
- Fluency in Python and strong proficiency in at least one systems or application language such as Java, Go, Rust, or TypeScript.
- Hands-on knowledge of tool calling, structured generation, retrieval, context engineering, prompt management, and model APIs.
- Experience with production observability, including structured traces, replay, metrics, logs, and incident diagnosis.
- Ability to balance agent quality with latency, reliability, security, and inference cost.
- Track record of setting technical direction and delivering results across organizational boundaries.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Clear written and verbal communication with engineering, product, and leadership audiences.
Nice to Have
- Building evaluation or observability infrastructure for agentic coding, data engineering, or analytics systems.
- Designing human-evaluation programs, scoring rubrics, annotation workflows, or grader-calibration methods.
- Working with multi-agent orchestration, long-running agents, asynchronous workflows, or durable execution.
- Developing synthetic tasks, simulations, adversarial tests, red-team exercises, or safety guardrails.
- Building retrieval systems that use vector search, hybrid search, semantic indexing, ranking, or caching.
- Operating multi-tenant systems that process sensitive enterprise data.
- Working with model training, fine-tuning, reinforcement learning, or feedback-driven optimization.
- Evaluating and onboarding frontier models based on measured product outcomes.
- Experience with databases, SQL engines, data platforms, Kubernetes, or cloud-native infrastructure.
We Offer
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
About the Company
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.
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
© Snowflake. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Cloud Computing,Data Management,Artificial Intelligence
About the Company Snowflake is a cloud-native data platform launched in 2012 by a team of data experts who identified limitations in traditional databases. The company has a strong presence in Poland, with a technical hub in Warsaw. Snowflake offers an international work environment with opportunities for skill development and collaboration with industry experts. Products, Services & Tech Stack Core Solutions: Data processing and management platform. Technologies & Frameworks: Specific technologies and frameworks are not detailed in the provided text. Project Scope & Target Clients Client Base: Not specified. Engineering Scale: Not specified.
More at Snowflake
All 358 rolesSenior Data Scientist - Product
Snowflake · United States
Account Executive, Enterprise Acquisition
Snowflake · United States
Solution Engineer
Snowflake · Japan
Account Executive - Expansion
Snowflake · Netherlands