EVERSANA
Posted 68 days agoVerified live 1d ago
Senior AI Application Engineer
Brief overview
Remote
PhDOr in progress
$178k–$215k/yrStated range
7+ yrsMinimum
62 H-1B approvalsDept. of Labor
6 green cardsCertified filings
PythonTypeScriptRustGenerative AILarge Language Models (LLMs)Cognitive ArchitecturesMulti-agent SystemsAgentic Design PatternsLLM APIs OpenAILLM APIs AnthropicLLM APIs Google GeminiOpen-weight Models Llama 3Open-weight Models MistralVector DatabasesGraph DatabasesRetrieval-Augmented Generation (RAG) ArchitecturesCloud Architecture AWS
About the company
EVERSANAeversana.com
EVERSANA is the provider of global services to the life science industry.
Visa sponsorship history
4 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.62H-1B approved
97%approval rate
11new H-1B hires
6PERM certified
$102,846median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202327
20249
202518
20268
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20238
20244
20258
20264
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20232
20241
20253
Top sponsored roles
IT Software Quality Engineering LeadAssociate Director, SEOSr. Data EngineerSr. Engineer, Tagging SolutionsSr. Business Analyst
Sponsored employees from
India
Job description
Summary
EVERSANA is a global company committed to creating a healthier world through innovative commercialization services in the life sciences industry. They are seeking a Senior AI Application Engineer to develop agentic systems and optimize data pipelines, working closely with the Chief AI & Analytics Officer.
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
- 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)
- 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
- Expert-level proficiency in Rust
- Extensive experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search)
Qualifications
Must Haves
- 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)
Nice to Haves
- 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
- Expert-level proficiency in Rust
- Extensive experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search)
More jobs like this
