Ph.D. in Computer Science, Engineering (Electrical, Mechanical, Chemical), Mathematics, Physics, Artificial Intelligence, Software Engineering, or a closely related field.
Experience in enterprise scale deployment of multi-agent architectures.
Patient Minded I act with the patient's best interest in mind.
Client Delight I own every client experience and its impact on results.
Take Action I am empowered and empower others to act now.
Grow Talent I own my development and invest in the development of others.
Win Together I passionately connect with anyone, anywhere, anytime to achieve results.
Communication Matters I speak up to create transparent, thoughtful and timely dialogue.
Embrace Diversity I create an environment of awareness and respect.
Always Innovate I am bold and creative in everything I do.
All your information will be kept confidential according to EEO guidelines.
EVERSANA is committed to providing competitive salaries and benefits for all employees. If this job posting includes a base
Benefits
Equity / stock options
Additional Information
THE POSITION :
As a Mid-Level AI / Agent Application Engineer, you will be the core builder of the organization's new agentic workforce. Working under the guidance of the Chief AI & Analytics Officer, you will develop the actual agents, write the APIs (tools) the agents will use, and optimize the data pipelines that feed context to the AI.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Our employees are tasked with delivering excellent business results through the efforts of their teams. These results are achieved by:
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.
EXPECTATIONS OF THE JOB:
Travel : Some travel may be required for meeting with clients, stakeholders, or off-site personnel/management
Hours: 40 hours per week, Monday to Friday
The above list reflects the general details necessary to describe the expectations of the position and shall not be construed as the only expectations that may be assigned for the position.
An individual in this position must be able to successfully perform the expectations listed above.
MINIMUM KNOWLEDGE, SKILLS AND ABILITIES:
The requirements listed below are representative of the experience, education, knowledge, skill and/or abilities required.
7+ years of software engineering experience, with 3+ years specifically in generative AI, LLMs, or cognitive architectures.
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).
Eversana1 · New York, NY