Lead Software- solutions Architect
Role details
Job location
Tech stack
Job description
We are seeking a highly experienced Senior Software Architect to lead the design and development of scalable, AI-native enterprise platforms. This role combines strategic technical leadership with deep hands-on engineering expertise across distributed systems, AI infrastructure, data engineering, cloud platforms, and modern software architecture.
The ideal candidate will drive the architecture and implementation of intelligent systems that integrate structured enterprise data, unstructured content, LLM-powered workflows, vector search, APIs, and AI agents into a unified platform.
You will collaborate closely with executive leadership, product, research, engineering, and data science teams to deliver next-generation AI-driven products focused on research, knowledge management, workflow automation, and customer intelligence.
Senior Architect with deep expertise in AI-native platforms, RAG/LLM systems, distributed cloud architecture, and hands-on backend engineering (Python/Java) with vector DB and AI orchestration experience.", Architecture & Platform Engineering
- Design, build, and evolve scalable AI-native platform architectures
- Lead architectural decisions across:
- Cloud infrastructure
- Distributed systems
- APIs and microservices
- Data platforms
- AI orchestration frameworks
- Developer tooling
- Build systems capable of handling:
- Structured and unstructured data
- Embeddings and vector search
- Real-time AI workflows
- Knowledge retrieval systems
- Establish best practices around scalability, observability, security, performance, and reliability
- Architect hybrid data retrieval solutions leveraging SQL, NoSQL, graph, and vector database technologies
AI & Intelligent Systems
- Design and implement production-grade AI and LLM-powered applications
- Develop architectures for:
- Retrieval-Augmented Generation (RAG)
- Multi-agent AI systems
- Semantic and vector search
- Knowledge graphs
- AI-assisted workflow orchestration
- Automated content generation and validation
- Evaluate and integrate leading AI platforms, open-source models, and orchestration frameworks
- Build systems supporting prompt management, evaluation pipelines, observability, guardrails, and human-in-the-loop workflows
- Drive continuous AI model improvement and monitoring strategies
Hands-On Engineering Leadership
- Write and review high-quality production code
- Lead implementation of core platform components and reusable reference architectures
- Mentor engineering teams on modern cloud-native and AI-first development practices
- Establish CI/CD pipelines, testing frameworks, coding standards, and engineering best practices
- Champion AI-assisted software development workflows and automation tooling
Cross-Functional Collaboration
- Partner with product, research, data, and executive teams to translate business objectives into scalable technical solutions
- Align architecture strategy with long-term company vision and product roadmap
- Support hiring, mentoring, and scaling of high-performing engineering teams
- Lead technical initiatives across globally distributed teams, Experience designing and implementing systems using:
- Relational databases:
- PostgreSQL
- MySQL
- SQL Server
- NoSQL databases:
- MongoDB
- Cassandra
- DynamoDB
- Redis
- Vector databases and semantic retrieval systems:
- Pinecone
- Weaviate
- Milvus
- pgvector
- Qdrant
- Chroma
- Large-scale data pipelines, ETL/ELT architectures, and distributed data processing systems
AI & LLM Ecosystem
Hands-on production experience with:
- AI platforms and LLM providers:
- OpenAI
- Anthropic
- Google Gemini
- AWS Bedrock
- AI orchestration and agent frameworks:
- LangChain
- LangGraph
- LlamaIndex
- CrewAI
- AutoGen
- Haystack
- DSPy
- AI observability and evaluation tools:
- Langfuse
- Weights & Biases
- Arize Phoenix
- Helicone
- PromptLayer
- Embeddings, semantic search, RAG systems, and knowledge retrieval architectures
- AI evaluation pipelines, fine-tuning, quality monitoring, and governance frameworks
Requirements
- 10+ years of software engineering and architecture experience
- Proven expertise designing and building large-scale distributed systems
- Strong hands-on programming experience with:
- Java and/or C++
- Python
- Deep understanding of:
- API design
- Microservices architecture
- Event-driven systems
- Cloud-native application development
- Extensive experience with AWS cloud infrastructure (preferred)
Data & Platform Architecture, * Demonstrated success leading architecture initiatives for complex enterprise platforms
- Ability to balance strategic thinking with hands-on execution
- Strong communication and stakeholder management skills
- Experience mentoring senior engineers and leading cross-functional teams
- Comfortable operating in fast-paced, evolving, startup-style environments
- Experience managing and scaling geographically distributed engineering organizations
Ideal Candidate Profile
The successful candidate is:
- Passionate about building transformative AI-driven platforms
- A creative and practical technology leader with strong problem-solving abilities
- Highly collaborative and people-oriented
- A servant leader who leads by example and empowers teams
- Comfortable driving innovation while maintaining execution excellence
- Motivated by building impactful, scalable technology solutions, * Bachelor's degree in Computer Science, Engineering, Information Systems, or related field required
- Master's degree preferred
- Strong foundational understanding of software engineering principles, frameworks, and emerging technology trends
- Experience leading large-scale organizational and technical transformation initiatives