AI/ML Architect
Proffer It Consultancy · Warangal · onsite · Posted 21d ago
Undisclosed10–15 yrsfulltimeSourced from
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About this role
Position Name: AI/ML Architect
Location: Hyderabad (Onsite, 5 days per week)
Experience: 10-18 Years
About BinQle
BinQle is a global delivery and execution partner supporting enterprises across the US, India, Singapore and Australia. We specialize in structured hiring, managed teams, and long-term delivery support.
Role Summary:
Lead the technical delivery of enterprise AI/Agentic AI projects post deal-closure. Oversee architecture, design, build, deployment, and optimization of AI/ML systems, ensuring production-grade quality, scalability, and compliance.
What Youll Do:
- Own end-to-end technical architecture and solution integrity during project delivery
- Translate solution blueprints into detailed technical designs, backlogs, and integration plans
- Lead detailed design reviews and align with AI platform, MLOps, and Agentic AI best practices
- Select frameworks, APIs, libraries, and cloud-native services for implementation
- Serve as technical anchor for customer AI/ML and Agentic AI projects
- Guide engineering teams on modular, secure, and reusable implementation strategies
- Review and validate code, infrastructure scripts, and ML pipelines
- Oversee data pipelines, model training, LLMOps, and model deployment workflows
- Provide hands-on support for complex components such as LLM pipelines, vector stores, and fine-tuning
- Resolve system integration challenges across APIs, knowledge stores, and orchestration layers
- Implement or validate MLOps workflows using tools like MLflow, Airflow, Argo, KServe, BentoML
- Embed observability, safety, and compliance into the AI/ML lifecycle
- Integrate with AI governance platforms for model tracking, versioning, audits, and risk controls
- Ensure alignment with enterprise and regulatory standards (NIST AI RMF, EU AI Act, internal policies)
- Act as the technical point of contact for client-side engineering and data science teams
- Participate in sprint planning, status reviews, and change control boards
- Support knowledge transfer, UAT, documentation, and post-deployment handoffs
What We re Looking For (Must-Haves):
- Exposure to agent orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI)
- Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups
- Exposure to regulatory/ethical concerns in AI (fairness, transparency, bias mitigation)
- Familiarity with AI observability, explainability, and governance tooling (Arize, Fiddler, TruEra)
Qualifications:
B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field
Disclaimer: This job posting and Location 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.
Location: Hyderabad (Onsite, 5 days per week)
Experience: 10-18 Years
About BinQle
BinQle is a global delivery and execution partner supporting enterprises across the US, India, Singapore and Australia. We specialize in structured hiring, managed teams, and long-term delivery support.
Role Summary:
Lead the technical delivery of enterprise AI/Agentic AI projects post deal-closure. Oversee architecture, design, build, deployment, and optimization of AI/ML systems, ensuring production-grade quality, scalability, and compliance.
What Youll Do:
- Own end-to-end technical architecture and solution integrity during project delivery
- Translate solution blueprints into detailed technical designs, backlogs, and integration plans
- Lead detailed design reviews and align with AI platform, MLOps, and Agentic AI best practices
- Select frameworks, APIs, libraries, and cloud-native services for implementation
- Serve as technical anchor for customer AI/ML and Agentic AI projects
- Guide engineering teams on modular, secure, and reusable implementation strategies
- Review and validate code, infrastructure scripts, and ML pipelines
- Oversee data pipelines, model training, LLMOps, and model deployment workflows
- Provide hands-on support for complex components such as LLM pipelines, vector stores, and fine-tuning
- Resolve system integration challenges across APIs, knowledge stores, and orchestration layers
- Implement or validate MLOps workflows using tools like MLflow, Airflow, Argo, KServe, BentoML
- Embed observability, safety, and compliance into the AI/ML lifecycle
- Integrate with AI governance platforms for model tracking, versioning, audits, and risk controls
- Ensure alignment with enterprise and regulatory standards (NIST AI RMF, EU AI Act, internal policies)
- Act as the technical point of contact for client-side engineering and data science teams
- Participate in sprint planning, status reviews, and change control boards
- Support knowledge transfer, UAT, documentation, and post-deployment handoffs
What We re Looking For (Must-Haves):
- End-to-End AI Solution Architecture and Production System Design
- Machine Learning Lifecycle (MLLC) and Production AI Pipelines
- AI Model Optimization, Scalability, and Performance Tuning
- Hands-on Experience with Large Language Models (GPT, Llama, Gemini, Claude)
- Retrieval-Augmented Generation (RAG) and Vector Databases
- Prompt Engineering, Fine-tuning (PEFT/LoRA), and Agentic AI Frameworks
Good to Have (Optional - only if mentioned): - Exposure to agent orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI)
- Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups
- Exposure to regulatory/ethical concerns in AI (fairness, transparency, bias mitigation)
- Familiarity with AI observability, explainability, and governance tooling (Arize, Fiddler, TruEra)
Qualifications:
B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field
Disclaimer: This job posting and Location 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.
Sourced from naukri
Skills
claudeCrewaiapisai modelai frameworksapache airflowauditsgeminiChange Controlglobal deliveryai governancedeploymentFiddlercloudArchitecturecomplianceAi PlatformLangchainData PipelineData ScienceArtificial Intelligence