Website:
trusys.ai
Job details:
Company Description Trusys provides an AI safety and compliance guardrail layer that enables enterprises to deploy AI solutions with confidence. Its platform integrates with LLM endpoints, voice bots, RAG pipelines, and agentic workflows to continuously monitor and validate AI behavior. Trusys runs proprietary hallucination detectors, adversarial red-team probes, and drift monitors to identify and mitigate risks in real time. All results are mapped to industry-standard frameworks such as the EU AI Act, NIST RMF, and MITRE, generating machine-verifiable evidence that supports audits, compliance, and risk management teams.
Key Responsibilities
- Design, develop, and maintain scalable enterprise integrations using Java and Spring Boot.
- Build and integrate RESTful APIs, web services, microservices, and third-party platforms.
- Develop secure and reliable integration solutions between internal applications, SaaS platforms, databases, and external systems.
- Design Agentic AI integrations that enable AI agents to interact with enterprise applications, APIs, databases, and business workflows.
- Integrate LLMs and AI services into enterprise applications and automation workflows.
- Develop tools, APIs, and services that allow AI agents to securely access and perform actions across enterprise systems.
- Implement agent workflows involving tool calling, function calling, orchestration, memory, and multi-step task execution.
- Work with AI/ML engineers to integrate LLM-based capabilities into production applications.
- Design event-driven architectures using technologies such as Kafka, messaging queues, or similar platforms.
- Develop robust error handling, retry mechanisms, logging, monitoring, and observability for integration services.
- Ensure integrations meet requirements for security, scalability, reliability, and performance.
- Collaborate with architects, backend engineers, frontend engineers, AI engineers, and business stakeholders to define integration requirements.
- Troubleshoot complex integration issues across distributed systems and external APIs.
- Participate in code reviews, architecture discussions, technical documentation, and engineering best practices.
- Contribute to CI/CD automation and deployment processes for integration services.
- Evaluate emerging AI and Agentic AI technologies and identify opportunities to improve enterprise workflows through intelligent automation.
Required Technical Skills
Backend & Integration
- Strong hands-on experience with Java 8/11/17+.
- Strong experience with Spring Boot, Spring Framework, and REST APIs.
- Experience developing microservices and distributed applications.
- Strong understanding of API design, authentication, authorization, and integration patterns.
- Experience with JSON, XML, HTTP, OAuth 2.0, JWT, and API security.
- Experience integrating third-party and enterprise applications.
Agentic AI & LLM
- Understanding of Generative AI, Large Language Models (LLMs), and Agentic AI architectures.
- Experience integrating AI/LLM APIs into enterprise applications.
- Knowledge of AI agents, tool/function calling, agent orchestration, and workflow automation.
- Experience working with frameworks or platforms such as LangChain, LangGraph, Semantic Kernel, or similar technologies is highly desirable.
- Understanding of RAG, embeddings, vector databases, and prompt engineering.
- Experience designing secure interfaces through which AI agents can interact with enterprise systems is a strong plus.
Cloud & DevOps
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Docker and containerized applications.
- Experience with CI/CD tools and modern DevOps practices.
- Knowledge of Kubernetes is a plus.
Messaging & Data
- Experience with Apache Kafka or other messaging/event-streaming technologies.
- Working knowledge of relational and NoSQL databases.
- Understanding of event-driven architecture and asynchronous processing.
Preferred Qualifications
- Experience building AI-powered enterprise integrations or automation platforms.
- Experience integrating LLMs such as OpenAI, Anthropic, Gemini, or equivalent models.
- Familiarity with Model Context Protocol (MCP) or similar approaches for connecting AI agents with tools and enterprise data.
- Experience with vector databases such as Pinecone, Weaviate, Milvus, or pgvector.
- Knowledge of observability tools such as OpenTelemetry, Splunk, Datadog, or Grafana.
- Understanding of enterprise integration platforms and API gateways.
- Experience working in Agile/Scrum environments.
Education & Experience
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline.
- 4+ years of professional software/integration engineering experience, with strong hands-on Java development experience.
- Demonstrated experience designing and implementing enterprise-grade integrations.
- Experience with Generative AI or Agentic AI projects is strongly preferred.
Key Competencies
- Strong problem-solving and analytical abilities.
- Ability to understand complex enterprise systems and integration dependencies.
- Strong understanding of software architecture and integration patterns.
- Excellent communication and collaboration skills.
- Ability to work effectively across engineering, product, data, and AI teams.
- Strong ownership mindset with a focus on delivering reliable, production-ready solutions.
- Passion for emerging AI technologies and intelligent automation.
- rations.
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