Experience
: 4.00 + years
Salary
: INR 5000000-8000000 / year (based on experience)
Expected Notice Period
: 30 Days
Shift
: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type
: Office ()
Placement Type
: Full Time Permanent position(Payroll and Compliance to be managed by: Ciroos)
(*Note: This is a requirement for one of Uplers' client - Ciroos)What do you need for this opportunity?Must have skills required:Multi-Agent Systems, SaaS development, AI/ML technologies, Go or Rust (preferred), model optimization, Python (advanced), AWS, GCP, or AzureCiroos is Looking for:Software Engineer - Agentic AI & Multi-Agent SystemsPosition Overview
We are seeking a skilled Software Engineer with 3-5 years of experience to join our cutting-edge Multi-Agent SaaS platform focused on Observability and Security. You will design, develop, and deploy autonomous AI agents that can reason, plan, and execute complex tasks with minimal human intervention. This role requires deep expertise in Large Language Models (LLMs), advanced fine-tuning techniques, and multi-agent orchestration systems.
Key Responsibilities
Agentic AI Development
- Design and implement autonomous AI agents using state-of-the-art agentic frameworks (CrewAI, LangGraph, AutoGen, OpenAI Agents SDK)
- Develop multi-agent systems that can collaborate, negotiate, and coordinate to solve complex observability and security challenges
- Build agents capable of dynamic planning, reflection, and iterative improvement
- Implement tool-calling capabilities and structured output generation for agents
LLM Engineering & Fine-Tuning
- Fine-tune LLMs using advanced techniques including RLHF, PPO, DPO, and KTO
- Implement preference learning algorithms to align models with human feedback
- Optimize model performance through parameter-efficient methods (LoRA, Half Fine-Tuning)
- Develop and maintain training pipelines for continuous model improvement
Multi-Agent Architecture
- Design scalable multi-agent architectures with proper communication protocols
- Implement agent coordination mechanisms, task allocation, and load balancing
- Build fault-tolerant systems with agent supervision and failure recovery
- Develop standardized interfaces for agent interoperability using emerging protocols like MCP
Observability & Security Integration
- Implement comprehensive observability for AI agent systems using OpenTelemetry standards
- Develop monitoring solutions for agent behavior, performance, and decision-making processes
- Build security controls for multi-agent environments including access management and audit trails
- Create real-time dashboards for agent performance tracking and anomaly detection
Required Technical Skills
Core AI/ML Technologies
- Frameworks: TensorFlow, PyTorch, Hugging Face Transformers, TRL (Transformer Reinforcement Learning)
- LLM Fine-Tuning: Hands-on experience with RLHF, PPO, DPO, and synthetic data generation
- Model Optimization: LoRA, QLoRA, gradient checkpointing, mixed precision training
- Evaluation: Model evaluation frameworks, reward model training, preference data collection
Agentic AI Frameworks
- Multi-Agent Platforms: CrewAI, LangGraph, AutoGen, LangChain, Semantic Kernel
- Agent Orchestration: Experience with agent planning, tool integration, and structured outputs
- Memory Systems: Vector databases (Pinecone, Weaviate, Chroma), RAG implementation
- Function Calling: Tool integration, API orchestration, external system connectivity
Software Engineering
- Languages: Python (advanced), Go or Rust (preferred)
- APIs: RESTful services, GraphQL, gRPC, WebSocket connections
- Databases: Vector databases, PostgreSQL, Redis, time-series databases
- Cloud Platforms: AWS, GCP, or Azure with containerization (Docker, Kubernetes)
Observability & Monitoring
- Tools: OpenTelemetry, Prometheus, Grafana, Jaeger, Zipkin
- Platforms: Datadog, New Relic, Splunk, or equivalent enterprise observability solutions
- AI Observability: LLM monitoring, trace analysis, model drift detection
- Metrics: Custom metric creation, alerting systems, performance dashboards
Experience Requirements
Professional Experience (3-5 years)
- Production deployment of LLM-based applications with real-world usage
- Experience with distributed systems and microservices architecture
- Track record of implementing and scaling AI/ML systems in production environments
- Familiarity with agile development practices and CI/CD pipelines
Domain-Specific Experience
- LLM Fine-Tuning: At least 1 year of hands-on experience with advanced fine-tuning techniques beyond basic supervised fine-tuning
- Multi-Agent Systems: Experience building systems with multiple interacting AI components
- Observability: Implementation of monitoring and logging systems for complex distributed applications
- SaaS Development: Understanding of multi-tenant architectures, API design, and cloud-native development`
How to apply for this opportunity?
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers:
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
