Note: The job is a remote job and is open to candidates in USA. EVERSANA provides commercialization services, products, and solutions to the life sciences and healthcare industries. The Mid-Level AI / Agent Application Engineer will build agentic workforce applications, develop agents and APIs, optimize AI data pipelines, and implement secure, scalable multi-agent systems.
Responsibilities
- Architect, design and implement scalable, multi-agent systems that automate complex, multi-step business processes
- Translate existing processes, and develop novel multi-agent architectures for new opportunities
- Implement agentic solutions leveraging agent orchestration frameworks (e.g., Google ADK, LangGraph, CrewAI, etc.)
- Design secure "tool-calling" architectures, allowing LLMs to interact with internal databases, CRMs, and APIs safely
- Implement LLMOps/AgentOps best practices
- Mitigate AI-specific security risks, such as prompt injection, hallucination loops, and unauthorized tool execution
- Demonstrate a commitment to diversity, equity, and inclusion through continuous development, modeling inclusive behaviors, and proactively managing bias
- All other duties as assigned
Skills
- • Travel: Some travel may be required for meeting with clients, stakeholders, or off-site personnel/management
- • Hours: 40 hours per week, Monday to Friday
- • Ph.D. in Computer Science, Engineering (Electrical, Mechanical, Chemical), Mathematics, Physics, Artificial Intelligence, Software Engineering, or a closely related field
- • 1 - 7+ years of software engineering experience
- • Expert-level proficiency in Python and/or TypeScript
- • Experience with MCP architectures
- • Proficiency in Rust
- • Deep understanding of agentic design patterns (e.g., ReAct, Plan-and-Solve, Reflection, Tree of Thoughts, etc.)
- • Extensive experience with LLM APIs (OpenAI, Anthropic, Google Gemini) and open-weights models (Llama 3, Mistral, etc.)
- • Experience with vector and graph databases
- • Experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search)
- • Strong background in cloud architecture (AWS, GCP, or Azure) and containerization (Docker/Kubernetes)
- • Experience in enterprise scale deployment of multi-agent architectures
- • Expert-level proficiency in Rust
- • 3+ years specifically in generative AI, LLMs, or cognitive architectures
- • Extensive experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search)
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