Sr. AI Solutions Engineer required for a Full Time Remote position

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We are trying to source Sr. Software Engineer AI Solutions & Agent Workflows (Solutions Team) for our direct client.

It is a Full Time Remote position.

Role Summary:

We are hiring an AI Solutions Engineer to develop cloud-native agentic workflows for enterprise applications using LLMs. This role is focused on building and orchestrating intelligent agents (e.g., for RAG, code generation, data extraction, time series analysis) that integrate with business systems and are optimized for deployment across multi-cloud environments.

Responsibilities:

• Design and develop AI agent workflows (e.g., RAG, CodeGen, Multimodal, Time-Series) based on MisaCore containerized agent architecture.
• Build orchestration pipelines for chaining specialized agents using REST, gRPC, WebSockets, and event-driven architectures.
• Implement multi-agent collaboration, context-passing, and escalation logic to human-in-the-loop where needed.
• Integrate vector databases (e.g., FAISS, Qdrant) and fine-tune retrieval performance with semantic embedding models.
• Package agents into deployable containers with Kubernetes manifests, Helm charts, and horizontal scaling logic.
• Create APIs (REST/GraphQL) for real-time agent interaction and OpenAI-compatible endpoints for customers.
• Collaborate with the infrastructure team to optimize agent performance for the target hardware environment.

Ideal Experience:

• 3 6 years experience building full-stack AI solutions using open-source LLMs (e.g., LLaMA, Mistral, Falcon, CodeBERT).
• Experience creating agentic workflows with LangChain, Haystack, or custom LLM toolchains.
• Proficiency in Python, containerization (Docker), and LLM framework stacks (Transformers, PyTorch, Hugging Face).
• Familiarity with RAG architectures, embedding models, and chunking strategies.
• Experience deploying AI services on cloud platforms (OCI, AWS, Azure, Google Cloud Platform) is highly desirable.
• Bonus: Understanding of multi-agent systems, distributed inference, and model hot-swapping.