Job description

• Design, develop, and deploy Generative AI and automation solutions for public-sector use cases. • Build and operationalize Custom GPTs, AI agents, domain-specific copilots, and agentic workflows . • Develop end-to-end AI/ML pipelines covering data ingestion, model training, evaluation, deployment, and monitoring. • Build RAG-based solutions using vector databases such as Pinecone, FAISS, or Weaviate. • Integrate AI solutions using OpenAI APIs, LangChain, LlamaIndex, and related Generative AI frameworks. • Develop AI applications using Python and/or R and cloud platforms such as Azure, AWS, or GCP. • Apply machine learning techniques including supervised learning, unsupervised learning, neural networks, and model evaluation. • Work directly with customers to understand business requirements and translate them into technical AI solutions. • Lead AI workshops, training sessions, POCs, and pilot implementations for technical and non-technical stakeholders. • Provide guidance on responsible AI, security, privacy, governance, and AI adoption. • Create technical documentation, playbooks, best practices, and maintenance guidelines. • Collaborate with cross-functional teams to scale successful AI initiatives into production. Required Qualifications: • 8+ years of experience in Generative AI, Custom GPTs, Agentic AI, Python development, RAG, and solution design . • Strong experience designing and implementing AI/ML solutions and automation workflows. • Hands-on experience with OpenAI APIs, LangChain, LlamaIndex, or similar frameworks. • Strong understanding of RAG architectures and vector databases. • Experience with cloud platforms and MLOps practices. • Strong customer engagement, communication, presentation, and training skills. • Experience translating business requirements into scalable AI solutions. • Understanding of AI security, privacy, governance, and responsible AI practices.

Requirements

Must-haves

Design, develop, and deploy Generative AI and automation solutions for public-sector use cases.
Build and operationalize Custom GPTs, AI agents, domain-specific copilots, and agentic workflows .
Develop end-to-end AI/ML pipelines covering data ingestion, model training, evaluation, deployment, and monitoring.
Build RAG-based solutions using vector databases such as Pinecone, FAISS, or Weaviate.
Integrate AI solutions using OpenAI APIs, LangChain, LlamaIndex, and related Generative AI frameworks.
Develop AI applications using Python and/or R and cloud platforms such as Azure, AWS, or GCP.
Apply machine learning techniques including supervised learning, unsupervised learning, neural networks, and model evaluation.
Work directly with customers to understand business requirements and translate them into technical AI solutions.
Lead AI workshops, training sessions, POCs, and pilot implementations for technical and non-technical stakeholders.
Provide guidance on responsible AI, security, privacy, governance, and AI adoption.
Create technical documentation, playbooks, best practices, and maintenance guidelines.
Collaborate with cross-functional teams to scale successful AI initiatives into production.
8+ years of experience in Generative AI, Custom GPTs, Agentic AI, Python development, RAG, and solution design .
Strong experience designing and implementing AI/ML solutions and automation workflows.
Hands-on experience with OpenAI APIs, LangChain, LlamaIndex, or similar frameworks.
Strong understanding of RAG architectures and vector databases.
Experience with cloud platforms and MLOps practices.
Strong customer engagement, communication, presentation, and training skills.
Experience translating business requirements into scalable AI solutions.
Understanding of AI security, privacy, governance, and responsible AI practices.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythonazureawsgcpmachine learning

Platform: careers-page
Effort: medium