Prompt Engineer ML Engineer

Prompt Engineer / ML Engineer

Infosys

Only for Sunnyvale we can negotiate on the cost rest location is MSA.

Location : Sunnyvale Austin Raleigh

Webex hire

Must have: Good understanding of FinOps and tooling and is an expert in distributed systems

Key Responsibilities

• Prompt Engineering Excellence: Design test and optimize system prompts and feature-specific prompts that shape Claudes behavior across consumer and API products.
• Evaluation Development: Build and maintain comprehensive evaluation suites that ensure model quality and consistency across product launches and updates.
• Cross-functional Collaboration: Partner closely with product teams research teams and safeguards to ensure new features meet quality and safety standards.
• Model Launch Support: Play a critical role in model releases ensuring smooth rollouts and catching regressions before they impact users.
• Infrastructure Contribution: Help build and improve the frameworks and tools that allow teams to develop and test prompts and features with confidence.
• Knowledge Transfer: Mentor product engineers on prompt engineering best practices and help teams build their first evaluations.
• Rapid Iteration: Work in a fast-paced environment where model capabilities advance daily requiring quick adaptation and creative problem-solving.

Required Qualifications

• 5 years of software engineering experience with Python or similar languages.
• Demonstrated experience with LLMs and prompt engineering (through work research or significant personal projects).
• Strong understanding of evaluation methodologies and metrics for AI systems.
• Excellent written and verbal communication skills youll need to explain complex model behaviors to diverse stakeholders.
• Ability to manage multiple concurrent projects and prioritize effectively.
• Experience with version control CI/CD and modern software development practices.

Preferred Qualifications

• Experience with Claude or other frontier AI models in production settings.
• Background in machine learning NLP or related fields.
• Experience with A/B testing and experimentation frameworks (e.g. Statsig).
• Familiarity with AI safety and alignment considerations.
• Experience building tools and infrastructure for ML/AI workflows.
• Track record of improving AI system performance through systematic evaluation and iteration.