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Job Description
- Partner directly with client engineering and business stakeholders to translate complex requirements into robust technical specifications and AI workflows.
- Architect and deploy production-grade AI solutions—including RAG pipelines, fine-tuned models, vector databases, and agent frameworks—within client cloud or on-premises environments.
- Lead integration efforts to connect AI microservices with existing enterprise infrastructure, legacy data stores, APIs, and business systems.
- (Senior/Team Lead) Act as the primary technical authority and trusted advisor to client executive leadership (CTOs, VPs of Engineering) on AI strategy, security, and ROI.
- Design data orchestration pipelines, vector search infrastructure (e.g., Pinecone, Qdrant, Milvus, PGVector), and framework integrations (e.g., LangChain, LlamaIndex, Semantic Kernel).
- Optimize model latency, throughput, token usage, and computing costs (FinOps) for high-scale enterprise workloads.
- Implement robust evaluation, observability, and safety frameworks to monitor accuracy, drift, hallucinations, and security guardrails in production.
- (Senior/Team Lead) Design distributed systems that meet enterprise compliance and regulatory standards (e.g., HIPAA, GDPR, SOC 2).
- Establish clean code bases, automated testing, CI/CD pipelines, and enterprise MLOps/LLMOps best practices.
- Troubleshoot performance bottlenecks, system outages, and deployment issues within customer environments.
- Conduct technical enablement and knowledge transfer sessions to empower client internal engineering teams.
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- (Senior/Team Lead) Oversee cross-functional delivery teams, mentor intermediate/junior engineers, conduct code reviews, and build reusable engineering playbooks.
- Experience: 3–8+ years in software design, solution engineering, or systems architecture, including proven experience building and deploying production enterprise AI/ML solutions.
- Core Languages: Fluency in Python and modern software engineering practices (TypeScript/Node.js or Go is a plus).
- AI Tech Stack: Expertise with modern AI stacks—PyTorch/TensorFlow, Hugging Face, OpenAI/Anthropic APIs, vector databases, prompt engineering, and agent frameworks.
- Cloud & DevOps: Deep hands-on experience with major cloud providers (AWS, Azure, or GCP), containerization (Docker), CI/CD, and infrastructure concepts (Kubernetes/Terraform preferred for Senior candidates).
- Communication: Outstanding technical communication and stakeholder management skills with the ability to explain complex AI trade-offs to non-technical business leaders.
- Preferred Certifications & Qualifications
Skills
PythonTypeScriptGoNode.jsMicroservicesTensorFlowPyTorchHugging FaceLangChainLLMPrompt EngineeringRAGMLOpsAWSAzureIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
About Company
Important dates & deadlines?
Application Deadline
20 Nov 26, 03:24 PM IST
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