About Trustero Trustero is an advanced AI application, purpose-built for the Security and Compliance vertical. Our patented AI agents can accurately and consistently do the most time-consuming jobs in Governance, Risk, and Compliance, like perform gap analysis, provide remediation guidance, questionnaire automation, evidence collection + mapping, and more, saving companies hundreds-of-thousands of dollars and returning 100s of valuable working hours each month.
Role Overview As a
Senior AI Engineer at Trustero, you will play a crucial role in optimizing/evaluating large language models (LLMs) for reasoning and decision-making processes, as well as implementing RAG pipelines and agentic architectures/workflows.
You will work closely with our engineering team to implement cutting-edge LLM/RAG techniques that enhance the intelligence and performance of our AI driven Governance, Risk and Compliance platform.
The ideal candidate has hands-on experience integrating LLMs and working with RAG pipelines, and is passionate about applying these technologies to deliver tangible impact. Familiarity with NLP and ML methods-particularly text classification-or experience fine-tuning LLMs for specific industry verticals would be highly desirable.
Salary Range: $150,000 - $220,000 USD per year, plus stock options, based on experience and qualifications.
Key Responsibilities - LLM Integration & Reasoning
- Develop LLM-based reasoning techniques, including automated decision-making and context understanding.
- Integrate LLM solutions into the core product to enhance user experiences and streamline compliance workflows.
- RAG Pipeline & Optimization
- Proficiency in chunking large documents and creating efficient indexes for retrieval-augmented generation.
- Experience running queries on RAG databases or vector stores to retrieve relevant context.
- Skill in re-ranking and optimizing results to provide the highest-quality context for LLM queries.
- Collaboration & Engineering
- Collaborate with the engineering team to integrate LLM solutions into our infrastructure, ensuring compatibility and scalability.
- Partner with product managers and engineers to align functionality with the product vision and deliver tangible user value.
- Conduct code reviews, write clean, maintainable code, and follow software engineering best practices.
- Continuous Improvement
- Continuously experiment with cutting-edge ML techniques and frameworks, particularly those related to LLMs and emerging technologies.
- Monitor and evaluate LLM system performance in production, iterating on solutions and model selection to ensure high reliability.
Salary Range: $150,000 - $220,000 USD per year.
Requirements - 5+ years of software engineering experience with a focus on ML, NLP, LLMs, or RAG.
- Bachelor's degree in Computer Science, Software Engineering, or a related field (advanced degrees are a plus).
- Proven track record with large language models (LLMs), applying them to reasoning and decision-making tasks.
- Expertise in LLM pipelines and RAG frameworks (e.g., Haystack, LlamaIndex, LangChain) and strong programming skills in Python or similar languages.
- Solid understanding of cloud platforms (AWS, GCP, or Azure) for production deployment and performance monitoring.
- Excellent collaboration and communication skills, able to work effectively with cross-functional engineering teams.
- Strong problem-solving abilities, adept at navigating complex technical challenges in a fast-paced environment.
Preferred Qualifications - Proficiency in Go, TypeScript, gRPC, and Protocol Buffers (Protobuf).
- Hands-on experience with LLM model tuning and performance benchmarking.
- Familiarity with NLP and ML techniques for text classification.
- Exposure to compliance, governance, or security-related platforms.
- Knowledge of microservices architecture, DevOps, and containerization tools (Docker, Kubernetes).