Lead the design and implementation of production AI/ML systems, including LLM applications, RAG pipelines, multimodal data pipelines, APIs, and MLOps workflows. Deploy and operate models on AWS using SageMaker, Lambda, S3, Glue, EKS, and Bedrock. Implement CI/CD, monitoring, retraining, governance, data quality controls, secure handling of sensitive data, and responsible AI guardrails.
This is a remote position.
Job Description:
Build AI Systems (Core Responsibility)
- Design and implement end-to-end AI/ML solutions including LLM-based applications
- Build RAG pipelines using vector databases and enterprise data sources
- Build machine learning models that automate their training, validation, monitoring, and retraining
- Develop APIs and services to operationalize AI capabilities across the organization
Develop Data + AI Pipelines
- Build ingestion for multimodal content and transformation pipelines for structured and unstructured data
- Integrate AI workflows with enterprise systems (policy, claims, billing, etc.)
- Ensure data quality, traceability, reliability, and governance in all AI pipelines
Operationalize Models (MLOps)
- Implement CI/CD for AI/ML workflows
- Deploy, monitor, and maintain models in production
- Manage model versioning, performance monitoring, and retraining processes
Build on AWS
- Develop solutions using: Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services
- Contribute to evolving use of AWS Bedrock
Apply Responsible AI Practices
- Implement guardrails for LLM-based systems (grounding, validation, safety)
- Ensure secure handling of sensitive data (PII, financial, etc.)
- Build systems aligned with enterprise governance and compliance standards
Qualifications:
Required
- 10+ years in software, data engineering, 5 years AI/ML engineering
- Hands-on experience building production AI/ML systems
- Experience with RAG pipelines, LLMs, or NLP-based systems
- Experience with AWS Bedrock or similar GenAI platforms
- Experience with data pipelines and distributed systems
- Experience deploying and operating systems in AWS
- Working knowledge of MLOps practices (CI/CD, monitoring, versioning)
Preferred
- Experience with vector databases (Pinecone, Weaviate, etc.)
- Experience in regulated industries (insurance, finance, healthcare)
- Exposure to microservices and containerized environments (Docker, Kubernetes)
Requirements
Qualifications:
Required
- 10+ years in software, data engineering, 5 years AI/ML engineering
- Hands-on experience building production AI/ML systems
- Experience with RAG pipelines, LLMs, or NLP-based systems
- Experience with AWS Bedrock or similar GenAI platforms
- Experience with data pipelines and distributed systems
- Experience deploying and operating systems in AWS
- Working knowledge of MLOps practices (CI/CD, monitoring, versioning)
Preferred
- Experience with vector databases (Pinecone, Weaviate, etc.)
- Experience in regulated industries (insurance, finance, healthcare)
- Exposure to microservices and containerized environments (Docker, Kubernetes)
Benefits
Diversity Inclusion:
At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career.
Exavalu also promotes flexibility depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also have a welcome back program to help people get back to the mainstream after a long break due to health or family reasons.
Exavalu Chennai, Tamil Nadu, IND Office
Awfis, RAR Technopolis, 7th floor, 4/293, Old Mahabalipuram Road, Perungudi, , , Chennai, Tamilnadu, India
Similar Jobs
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Lead hands-on delivery of agentic AI solutions across Salesforce, Slack, and enterprise workflows. Design LLM-powered agents, multi-agent systems, RAG pipelines, semantic search, AI evaluation frameworks, and secure integrations. Build Salesforce components and Agentforce actions, implement CI/CD and observability, establish governance and fallback strategies, modernize legacy integrations, mentor engineers, evaluate AI platforms, and automate manual GTM processes.
Top Skills:
AgentcoreAgentforceApexAutogenAws BedrockCopadoCrewaiGithub ActionsJavaScriptJenkinsLangchainLanggraphLightning Web ComponentsLlamaindexMcpPythonRestRetrieval Augmented GenerationSalesforceSalesforce EinsteinSalesforce Platform EventsSemantic KernelSlackSoapTypescriptVector DatabasesVertex Ai
Hardware
Build and deploy full-stack AI applications integrating LLMs, RAG architectures, vector databases, and multi-agent systems. Develop Python backends, APIs, ingestion pipelines, responsive interfaces, and real-time dashboards. Design and optimize PostgreSQL databases, containerize applications with Docker and Kubernetes, manage AWS and GPU infrastructure, and operate Linux environments. Mentor developers, conduct demonstrations, evaluate emerging AI technologies, and improve reliability through testing, debugging, performance tuning, and quality processes.
Top Skills:
AWSDockerGpu ClustersKubernetesLean Six SigmaLinuxLlmsMulti-Agent SystemsPostgresPythonRagRestful ApisSQLVector Databases
Marketing Tech • Design
Lead the architecture and implementation of a production-grade generative AI media platform. Build reproducible, versioned pipelines, train LoRAs, integrate control techniques (ControlNet, IP-Adapter, inpainting), automate QC against product references, deploy internal tools, and partner with design to own the technical roadmap and enable creative teams.
Top Skills:
BlenderCadCode-First PipelinesComfyuiControlnetDiffusersGpu EnvironmentsInpaintingIp-AdapterLlm OrchestrationLoraNode-Based PipelinesPythonReference ConditioningVlm
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
