We are looking for a Senior AI Engineer / Agent Developer to join our consulting team and collaborate closely with one of our key clients in the pharmaceutical sector.

You will contribute to a strategic Data & Analytics initiative focused on building an enterprise-grade conversational analytics agent for governed clinical data, combining Generative AI, agentic systems, advanced analytics and data governance.

Scope & Main Responsibilities

Design and develop a conversational analytics agent covering natural-language understanding, text-to-SQL, query execution, answer synthesis, explainability and source citation.
Implement LLM agent architectures and orchestration patterns such as ReAct, plan-and-execute or multi-agent workflows.
Build guardrails for hallucination prevention, traceability, scope enforcement and responsible AI.
Integrate the agent with Snowflake, semantic-layer assets, business glossaries and KPI definitions.
Implement secure data-access controls including RBAC and row-level security.
Define and maintain structured AI evaluation frameworks covering SQL correctness, answer faithfulness, regression and drift.
Implement observability, tracing and performance monitoring for agent behaviour, latency, token usage and errors.
Establish CI/CD and automated regression testing for prompts, agent configurations and semantic artefacts.
Collaborate with Data, Platform, AI Governance and Clinical Analytics teams.

Requirements

Fluent English
Strong experience building LLM-based applications, text-to-SQL or conversational analytics solutions.
Strong hands-on experience with Python and advanced SQL.
Experience with LLM patterns including prompt engineering, function calling, tool use and agent orchestration.
Experience with Snowflake and familiarity with Snowflake Cortex capabilities.
Experience with LangGraph or similar agent frameworks.
Familiarity with evaluation tools such as Ragas or DeepEval and observability platforms such as LangSmith, Weights & Biases, Arize or equivalent.
Experience working in regulated or governance-first environments, including RBAC, auditability and responsible-AI controls.
Strong software-engineering, testing and CI/CD practices.
Experience within pharma, healthcare, life sciences or another regulated industry is highly valued.

Erforderliche Kompetenzen

LLM-based application developmentText-to-SQL implementationPython programmingAdvanced SQLLLM agent architectures and orchestration (ReAct, plan-and-execute, multi-agent)Prompt engineering, function calling and tool integrationAgent frameworks (e.g., LangGraph)Snowflake integration and familiarity with Snowflake CortexData governance in regulated environments (RBAC, row-level security, auditability)Responsible AI, hallucination prevention, explainability and source citationDesigning AI evaluation frameworks (SQL correctness, answer faithfulness, regression, drift)Observability, tracing and performance monitoring for ML/agent systems (e.g., LangSmith, Weights & Biases, Arize)CI/CD and automated regression testing for prompts, agent configurations and semantic assetsIntegration with semantic-layer assets, business glossaries and KPI definitionsCross-functional collaboration with Data, Platform, AI Governance and Clinical Analytics teams

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