Agentic AI Developer

About The Role

As an Agentic AI Developer, you will make an impact by designing, building, and deploying intelligent AI agents that enable autonomous reasoning, decision-making, and workflow execution at enterprise scale. You will be a valued member of our AI engineering team and work collaboratively with architects, data engineers, platform teams, business stakeholders, and client-facing technology teams to deliver innovative AI-powered solutions.

Responsibilities

• Design and develop AI agents capable of task planning, contextual reasoning, tool utilization, and multi-step execution.
• Build and deploy single-agent and multi-agent systems using frameworks such as LangChain, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
• Develop Generative AI solutions leveraging Large Language Models (LLMs), including Azure OpenAI, OpenAI, Anthropic, and related platforms.
• Implement Retrieval-Augmented Generation (RAG) solutions and integrate vector databases to enhance knowledge retrieval, semantic search, and contextual grounding.
• Integrate AI agents with enterprise platforms, APIs, data ecosystems, and business applications while ensuring security, scalability, performance, and responsible AI practices.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.
• 3–8 years of experience in software engineering, data engineering, machine learning, or a related technical discipline.
• Hands-on experience developing Generative AI or LLM-powered applications in production environments.
• Strong proficiency in Python and experience with AI/ML libraries and frameworks such as OpenAI SDK, Hugging Face, Transformers, or similar.
• Experience building AI agent solutions using frameworks such as LangChain, Semantic Kernel, CrewAI, AutoGen, or comparable technologies.
• Experience implementing RAG pipelines, embeddings, semantic search, and vector database solutions.
• Knowledge of REST APIs, microservices architecture, and enterprise application integration patterns.
• Experience working with cloud platforms such as Azure, AWS, or GCP, including AI services such as Azure OpenAI and Azure AI Studio.
• Ability to design scalable, secure, and reliable AI solutions while adhering to responsible AI and data privacy standards.
• Experience designing multi-agent orchestration and planner-executor architectures.
• Experience integrating AI solutions with enterprise platforms such as Databricks, Snowflake, Synapse, CRM systems, ERP platforms, or ServiceNow.
• Knowledge of workflow orchestration tools such as Airflow or Prefect.
• Experience with containerization and cloud-native technologies, including Docker and Kubernetes.
• Exposure to knowledge graphs, semantic reasoning, observability frameworks, and AI evaluation methodologies.
• Industry experience within Insurance, Financial Services, or other highly regulated enterprise environments.

Qualifications

• Experience designing multi-agent orchestration and planner-executor architectures.
• Experience integrating AI solutions with enterprise platforms such as Databricks, Snowflake, Synapse, CRM systems, ERP platforms, or ServiceNow.
• Knowledge of workflow orchestration tools such as Airflow or Prefect.
• Experience with containerization and cloud-native technologies, including Docker and Kubernetes.
• Exposure to knowledge graphs, semantic reasoning, observability frameworks, and AI evaluation methodologies.
• Industry experience within Insurance, Financial Services, or other highly regulated enterprise environments.

Skills

• Experience designing multi-agent orchestration and planner-executor architectures.
• Experience integrating AI solutions with enterprise platforms such as Databricks, Snowflake, Synapse, CRM systems, ERP platforms, or ServiceNow.
• Knowledge of workflow orchestration tools such as Airflow or Prefect.
• Experience with containerization and cloud-native technologies, including Docker and Kubernetes.
• Exposure to knowledge graphs, semantic reasoning, observability frameworks, and AI evaluation methodologies.
• Industry experience within Insurance, Financial Services, or other highly regulated enterprise environments.

Benefits

• Cognitive Health and Wellness Program
• Flexible Spending Account (FSA)
• Retirement Savings Plan (401(k))
• Disability Insurance
• Life Insurance
• Accidental Death and Dismemberment (AD&D) Insurance
• Short-Term and Long-Term Disability Insurance
• Voluntary Employee Benefit Association (VEBA) Trust
• Employee Stock Purchase Plan (ESPP)
• Parental Leave
• Family and Medical Leave Act (FMLA)
• Comprehensive Health and Dental Plans
• Prescription Drug Coverage
• Vision Care Coverage
• Wellness Programs
• Onsite Fitness Center
• Onsite Cafeteria
• Onsite Childcare
• Onsite Parental Support Services
• Onsite Employee Resource Groups
• Onsite Employee Assistance Program (EAP)
• Onsite Employee Recognition Program
• Onsite Employee Learning and Development Programs
• Onsite Employee Recognition Programs
• Onsite Employee Learning and Development Programs
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