We are seeking a highly skilled Generative AI Solution Architect with 7+ years of experience having strong backend development expertise, to design, implement, and scale AI-powered solutions across enterprise use cases. The ideal candidate combines deep technical knowledge of backend systems and cloud architectures with hands-on experience in applying Generative AI (GenAI) technologies to real-world problems. This role involves working closely with business stakeholders, data scientists, and engineering teams to design scalable, secure, and high-performing AI-driven applications.
Key Responsibilities- Architect end-to-end Generative AI solutions, integrating LLMs, vector databases, APIs, and cloud-native services.
- Define system architecture, data flows, and integration strategies between AI models and existing enterprise platforms.
- Ensure solutions are scalable, cost-efficient, secure, and aligned with compliance requirements.
- Lead backend development for AI-driven applications using modern frameworks (e.g., Python, Node.js).
- Build and optimize APIs, microservices, and middleware for serving and integrating AI models at scale.
- Implement best practices for caching, asynchronous processing, distributed computing, and high availability.
- Work with LLMs (e.g., GPT, Claude, LLaMA, Gemini), fine-tuning and prompt engineering for domain-specific use cases.
- Integrate vector databases (Pinecone, Weaviate, FAISS, Milvus, Redis) for semantic search, RAG (Retrieval-Augmented Generation), and personalization.
- Evaluate, benchmark, and recommend models, frameworks, and tools suitable for enterprise applications.
- Partner with data scientists, ML engineers, and product teams to translate business requirements into technical architectures.
- Mentor development teams on backend and AI integration best practices.
- Serve as a technical advisor in client or stakeholder discussions.
Required Qualifications- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
- 8+ years of experience in backend development with expertise in designing large-scale distributed systems.
- Strong proficiency in RESTful APIs, GraphQL, microservices architecture, and event-driven systems.
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Proven track record of integrating AI/ML solutions, ideally with Generative AI frameworks (LangChain, LlamaIndex, Hugging Face, OpenAI APIs).
- Deep understanding of databases (SQL, NoSQL, graph, vector) and data pipelines.
- Familiarity with MLOps practices (CI/CD for ML, model deployment, monitoring).
- Experience with retrieval-augmented generation (RAG) pipelines.
- Exposure to enterprise security, data governance, and compliance frameworks (e.g., GDPR, HIPAA).
- Knowledge of DevOps, infrastructure-as-code (Terraform, CloudFormation).
- Strong communication skills with the ability to engage both technical and non-technical stakeholders.
- Prior experience as a solution architect, technical lead, or backend lead engineer.
