Senior AI / ML Engineer
Level: Senior
Experience: 8 10 years
Function: AI / ML Engineering

Remote - Contract based requirement

Role Overview
As Senior AI / ML Engineer, you will own the intelligence layer of the platform the agent
reasoning, orchestration, and model-integration core that determines how agents are built, how
they reason, and how they act once deployed. You will design the systems that let users
compose multi-step, tool-using agents reliably and at scale.
Key Responsibilities
Design and build the agent orchestration and reasoning layer planning, tool calling,
multi-agent coordination, memory, and state management.
Integrate and abstract multiple LLM providers behind a unified, swappable model layer so
agents are not tied to a single model.
Build and optimize RAG pipelines, embeddings, vector search, and the memory systems
agents rely on.
Implement evaluation, guardrails, and observability for agent behavior accuracy, safety,
latency, and cost.
Develop the reusable agent primitives, prompt frameworks, and adaptation workflows that
the builder experience is composed from.
Optimize inference performance, throughput, and cost across the platforms runtime.
Contribute to the platforms AI Gateway a unified entry point for routing, rate-limiting,
caching, and managing traffic across multiple models and providers.
Embed AI Governance into the platform at a high level model and prompt versioning,
audit trails, usage policies, and responsible-AI controls over how agents are built and run.
Help define AI Security practices prompt-injection and jailbreak defenses, data privacy,
secrets handling, and safe tool / action execution for deployed agents.




Work with the full-stack and backend engineers to expose AI capabilities through clean,
well-documented APIs that the builder and runtime consume.

Required Skills Experience
8 10 years in software / ML engineering, with strong recent hands-on experience in LLMs
and agentic systems.
Hands-on experience with agent-builder / Agent OS platforms systems where users
build, deploy, and run AI agents whether through established frameworks or custom
built orchestration.
Practical experience with agent frameworks and orchestration approaches (e.g.
LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI, or equivalent custom systems).
Expert-level Python and fluency across the contemporary ML / LLM stack.
Strong understanding of RAG, vector databases (Pinecone, Weaviate, pgvector, Qdrant,
or similar), and embedding models.
Experience with model serving, inference optimization, and LLMOps.
Solid grasp of prompt engineering, agent evaluation, and safety / guardrails.
Working knowledge of AI Gateway concepts (model routing, rate-limiting, caching, multi
provider management), AI Governance (versioning, audit, usage policies, responsible AI),
and AI Security (prompt-injection defense, data privacy, secure tool execution).
Familiarity with cloud platforms (AWS / Azure / GCP) and containerized deployment.

Nice to Have
Experience fine-tuning or deploying open-weight models.
Contributions to open-source agentic / LLM projects.
Experience with streaming, function-calling, and tool-use protocols

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior AI / ML Engineer (Uttar Pradesh)
🏢 Sparix Global
📍 Uttar Pradesh