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We are CirrusLabs . Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values driven organization.
You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve.
You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented < AI/Agentic Engineer with FinOps> to join our team. If you're excited to be part of a winning team, CirrusLabs (http://www.cirruslabs.io) is a great place to grow your career.
Experience - 3-5 years
Location - Hyderabad(preferred) or Bangalore
Shift Timings - 2 PM - 11 PM IST
Role Overview
We are seeking an AI Engineer to join an AI enablement team supporting a large-scale FinOps and cloud cost optimization program for a Fortune 50 enterprise. This role sits at the intersection of agentic AI, chatbot development, and applied data science, with a strong emphasis on designing end-to-end workflows that allow AI models to interact with users, systems, and automations in production environments.
You will help design and implement chatbots and agent-driven systems that leverage LLMs, RAG pipelines, and decision logic, ensuring that model outputs are not isolated artifacts but are properly integrated into chat interfaces, orchestration layers, and downstream automations. While this role requires solid data science and ML foundations, it is primarily focused on AI engineering and real-world deployment, not academic modeling.
This is a hands-on role within a growing agentic AI delivery team, working closely with cloud, FinOps, and automation engineers.
Key Responsibilities
• Design and build chatbot workflows, including how models, tools, and data sources interact within conversational and agent-driven systems.
• Develop agentic AI workflows using frameworks such as LangChain, LangGraph,
or equivalent orchestration patterns.• Implement RAG pipelines that combine LLMs with structured and unstructured data sources for reasoning and decision-making.
• Build and integrate LLM-powered services where model outputs are surfaced via chat interfaces, APIs, or automation triggers.
• Design decision-making flows where agents invoke tools, APIs, databases, or cloud services as part of execution.
• Collaborate with cloud and platform teams to ensure AI components are deployable, scalable, and secure within CSP environments.
• Support evaluation, iteration, and refinement of AI behaviors, prompts, tools, and workflows over time.
• Document architectures, workflows, and assumptions to support maintainability and enterprise adoption.
Required Skills & Experience
• 3+ years of experience in AI engineering, applied ML, or data science, with demonstrated hands-on delivery.
• Strong Python proficiency and experience working with ML / AI frameworks.
• Hands-on experience with LLMs and chatbot or conversational AI systems, including workflow design.
• Practical experience with agentic AI concepts, such as tool invocation, decision routing, and orchestration logic.
• Experience designing or implementing RAG architectures (vector search, embeddings, retrieval pipelines).
• Working familiarity with at least one Cloud Service Provider (Azure, AWS, or GCP), including deploying or integrating AI services in cloud environments.
• Ability to think beyond model training and focus on where outputs live, how they are consumed, and how they drive action.
• Strong communication skills and comfort collaborating across engineering, platform, and business teams.
Preferred / Nice-to-Have Skills
• Experience standing up or working with MCP servers, tool servers, or agent runtime environments.
• Exposure to FinOps, cloud cost optimization, or infrastructure automation use cases.
• Familiarity with Azure OpenAI, AWS Bedrock, or GCP Vertex AI.
• Experience deploying AI components as APIs or microservices.• Exposure to MLOps or LLMOps practices (monitoring, versioning, evaluation, prompt management).
• Understanding of enterprise governance, security, and compliance considerations for AI systems.
Why Work With Us
• Work on real-world agentic AI systems, not experimental or isolated models.
• Join a high-impact AI enablement team supporting enterprise-scale FinOps and cloud transformation.
• Gain hands-on exposure to chatbots, agentic workflows, and production LLM systems in a CSP environment.
• Collaborate with experienced cloud, automation, and AI architects on emerging enterprise use cases.
• Opportunity to grow into advanced AI engineering and agent orchestration roles
Job ID: 147481123
Skills:
Networking, PowerShell, Bash, Dns, Linux Servers, Load Balancers, ARM templates, Storage, Terraform, Firewalls, Microsoft Azure, Python, Virtualization, Azure infrastructure services, Backup and DR solutions, Log Analytics, Bicep, Azure Monitor
Skills:
React, Docker, Kubernetes, Python, LangChain, self reflection mechanism, LLMs, memory state management, Go, AI Frameworks, Control Loops, MCP, RAG pipelines, API orchestration
Skills:
Gcp, Docker, Flask, FastAPI, Rest Apis, Azure, Kubernetes, Python, AWS, embeddings, agentic workflows, microservices architecture, retrieval strategies, chunking, RAG architectures
Skills:
Machine Learning, Deep Learning, Numpy, Pandas, Gcp, Pytorch, Docker, Azure, Kubernetes, Python, AWS, Data Processing, scikit-learn, prompt engineering, chain of thought techniques, Streamlit, feature engineering, document detail extraction
Skills:
Memory Management, Python, LangChain, orchestration frameworks, LangGraph, tool-calling RAG pipelines, multi-agent coordination, MCP servers, API integrations
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