Lead Software Solutions Architect
New
Fully remote work flexibility within the United States.Full-TimeLead
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- AWSPostgreSQLPythonJavaC++NosqlMicroservices
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; Master’s degree preferred.
- 10+ years of experience in software engineering, solution architecture, and large-scale enterprise platform development.
- Proven expertise designing and delivering distributed, cloud-native systems in complex production environments.
- Strong hands-on programming experience with Python and Java and/or C++.
- Deep knowledge of API design, microservices architectures, event-driven systems, and modern software engineering principles.
- Extensive experience working with AWS cloud services and enterprise-scale cloud infrastructure.
- Strong background in relational databases, including PostgreSQL, MySQL, and SQL Server, as well as NoSQL technologies such as MongoDB, Cassandra, DynamoDB, and Redis.
- Experience designing and implementing vector search solutions and semantic retrieval architectures using technologies such as Pinecone, Weaviate, Milvus, pgvector, Qdrant, or Chroma.
- Hands-on experience building production-grade AI and LLM-powered applications using leading AI platforms and orchestration frameworks.
- Strong understanding of RAG architectures, AI agents, embeddings, knowledge retrieval systems, model evaluation, governance, monitoring, and observability practices.
- Demonstrated success leading enterprise architecture initiatives, mentoring engineering teams, and influencing senior stakeholders.
- Excellent communication, leadership, problem-solving, and stakeholder management skills.
- Ability to balance strategic vision with hands-on execution in dynamic, rapidly evolving environments.
Responsibilities
- Lead the architecture, design, and evolution of scalable AI-native enterprise platforms supporting intelligent workflows, knowledge management, automation, and customer intelligence initiatives.
- Define technical strategy and architectural standards across cloud infrastructure, distributed systems, APIs, microservices, data platforms, AI orchestration frameworks, and developer tooling.
- Design and implement robust solutions that support structured and unstructured data processing, semantic search, vector retrieval, embeddings, and real-time AI-driven workflows.
- Architect and guide the development of advanced AI applications, including Retrieval-Augmented Generation (RAG), multi-agent systems, knowledge graphs, AI-assisted automation, and intelligent content generation.
- Establish best practices for security, scalability, observability, performance, reliability, and operational excellence across the technology ecosystem.
- Provide hands-on technical leadership through code reviews, architecture reviews, development of reusable frameworks, and implementation of critical platform components.
- Drive adoption of modern engineering practices, including CI/CD pipelines, testing frameworks, automation tools, and AI-assisted development methodologies.
- Collaborate with product, research, data science, and executive stakeholders to align technology investments with business objectives and long-term product strategy.
- Mentor engineering teams, support talent development initiatives, and lead complex technical programs across globally distributed teams.
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