Generative AI Solution Architect
2 days ago
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,
). - 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
.
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