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Senior Solutions Architect (AI / ML) - Contractual

Senior Solutions Architect (AI / ML) - Contractual

Proximity Worksin, null, India
8 hours ago
Job description

We are looking for a Senior Solutions Architect to design, develop, and scale innovative AI / ML-driven solutions. You will be responsible for architecting highly scalable, low-latency distributed systems optimized for AI / ML workloads. As a key technical leader, you will solve complex challenges, influence next-generation AI / ML infrastructures, and guide cross-functional teams to deliver state-of-the-art solutions for fast-growing startups and enterprise companies.

Be at the forefront of shaping next-generation AI / ML infrastructures, driving solutions for high-impact products across diverse industries. You'll have the opportunity to influence key architectural decisions and enable real-world applications that scale globally, ensuring innovation and efficiency at every step.

Requirements

You'll be responsible for —

Driving end-to-end GenAI architecture and implementation :

  • Design and deploy multi-agent systems using modern frameworks (LangGraph, CrewAI, AutoGen)
  • Architect RAG solutions with advanced vector store integration
  • Implement efficient fine-tuning strategies for foundation models
  • Develop synthetic data generation pipelines for training and testing

Leading ML infrastructure and deployment :

  • Design high-performance model serving architectures
  • Implement distributed training and inference systems
  • Establish MLOps practices and pipelines
  • Optimize cloud resource utilization and costs
  • Set up monitoring and observability solutions
  • Drivng technical excellence and innovation :

  • Define architectural standards and best practices
  • Lead technical decision-making for AI / ML initiatives
  • Ensure scalability and reliability of AI systems
  • Implement AI governance and security measures
  • Guide teams on advanced AI concepts and implementations
  • Overseeing production AI systems :

  • Manage model deployment and versioning
  • Implement A / B testing frameworks
  • Monitor system performance and model drift
  • Optimize inference latency and throughput
  • Ensure high availability and fault tolerance
  • Fostering collaboration and growth :

  • Mentor engineering teams on AI architecture
  • Collaborate with stakeholders on technical strategy
  • Drive innovation in AI / ML solutions
  • Share knowledge through documentation and training
  • Lead technical reviews and architecture discussions
  • You need —

    8+ years exoerience in software engineering or architecture, including :

  • 4+ years leading cross-functional GenAI / ML teams
  • Production experience with distributed AI systems
  • Enterprise-scale AI architecture implementation
  • To lead and architect enterprise-scale GenAI / ML solutions, focusing on :

  • Multi-agent orchestration using LangGraph, CrewAI, and AutoGen
  • Workflow automation with LlamaIndex, LangChain, and LangFlow
  • Agent coordination using LETTA framework
  • Integration of specialized agents for reasoning, planning, and execution
  • To design and implement sophisticated AI architectures incorporating :

    Advanced RAG systems using :

  • Vector databases (Chroma, Weaviate, Pinecone, Milvus)
  • Hybrid search with BM25 and semantic embeddings
  • Self-querying and recursive retrieval patterns
  • Fine-tuning strategies for foundation models :

  • PEFT methods (LoRA, QLoRA, Adapter-tuning)
  • Parameter-efficient training approaches
  • Instruction fine-tuning and RLHF
  • Multi-agent frameworks integrating :

  • Tool-use and reasoning chains
  • Memory systems (short-term and long-term)
  • Meta-prompting and reflection mechanisms
  • Agent communication protocols
  • Expertise in advance data generation and synthesis :

  • Synthetic data generation using Arigilla and PersonaHub
  • Privacy-preserving data synthesis
  • Domain-specific data augmentation
  • Quality assessment of synthetic data
  • Data balancing and bias mitigation
  • To architect high-performance ML serving infrastructure focusing on :

  • Model serving platforms (BentoML, Ray Serve, Triton)
  • Real-time processing with Ray, Kafka, and Spark Streaming
  • Distributed training using Horovod, DeepSpeed, and FSDP
  • vLLM and TGI for efficient inference
  • Integration patterns for hybrid cloud-edge deployments
  • To drive cloud architecture decisions across :

  • Kubernetes orchestration with Kubeflow and KServe
  • Serverless ML with AWS Lambda, Azure Functions, Cloud Run
  • Auto-scaling using HPA, KEDA, and custom metrics
  • Resource optimization with Nvidia Triton and TensorRT
  • MLOps platforms (MLflow, Weights & Biases, DVC)
  • Bonus points for —

  • Research publications in AI / ML
  • Open-source project maintenance
  • Technical blog posts on AI architecture
  • Conference presentations
  • AI community leadership
  • Benefits

    What you get —

  • Best in class salary : We hire only the best, and we pay accordingly.
  • Proximity Talks : Meet other designers, engineers, and product geeks — and learn from experts in the field.
  • Keep on learning with a world-class team : Work with the best in the field, challenge yourself constantly, and learn something new every day.
  • About us —

    We are Proximity — a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting-edge tech at scale. Here's a quick guide to getting to know us better :

  • Watch our CEO, Hardik Jagda, tell you all about Proximity.
  • Read about Proximity's values and meet some of our Proxonauts here.
  • Explore our website, blog, and the design wing — Studio Proximity.
  • Get behind the scenes with us on Instagram! Follow @ProxWrks and @H.Jagda
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