StatusNeo
Website:
statusneo.com
Job details:
Company Description StatusNeo is a Silicon Valley–headquartered consulting and engineering firm focused on making AI real, scalable, and outcome-driven for global enterprises. The company builds “Authentic AI,” embedding intelligence directly into how businesses decide, build, and operate rather than treating AI as isolated experiments. Its proprietary AuthenticAI™ and Decision Fabric frameworks connect strategy, data, systems, and execution into measurable business results. StatusNeo supports clients across the full transformation lifecycle—from strategic and domain consulting to product and platform engineering, AI-native SDLC and DevSecOps, and managed transformation and operations. The team works with leading organizations in financial services, telecom, healthcare, travel, retail, and high-tech across the US, EMEA, and APAC.
Role Description The Technical Architect – Artificial Intelligence is a full-time, on-site role based in Bengaluru South. This role is responsible for defining and owning end-to-end AI solution architectures, aligning them with client business objectives and StatusNeo’s AuthenticAI and Decision Fabric principles. Day-to-day responsibilities include collaborating with stakeholders to translate business needs into technical designs, selecting appropriate AI/ML frameworks and cloud services, and guiding engineering teams in implementing scalable, secure, and resilient AI platforms. The Technical Architect will review and optimize models and data pipelines, establish architecture and coding standards, and ensure solutions integrate effectively with existing enterprise systems. The role also includes mentoring technical teams, contributing to best practices and reference architectures, and supporting pre-sales activities through solution design and technical presentations.
Qualifications
- Candidates should possess strong skills in AI and machine learning solution design, including model selection, ML lifecycle management, and deployment of production-grade AI systems.
- Candidates should possess capabilities in data architecture and engineering, such as designing data pipelines, integrating heterogeneous data sources, and ensuring data quality and governance.
- Candidates should possess experience with cloud platforms and modern infrastructure, including using major public clouds (e.g., AWS, Azure, GCP) and containerization/orchestration technologies for scalable AI workloads.
- Candidates should possess solid software engineering and architectural skills, including microservices design, APIs, integration patterns, and application security and performance best practices.
- Candidates should possess strong consulting and stakeholder management skills, including requirements discovery, technical communication, and the ability to translate complex AI concepts into clear business value.
- Relevant qualifications such as a bachelor’s or master’s degree in Computer Science, Engineering, Data Science, or a related field, along with experience in enterprise environments and leading cross-functional technical teams, are highly beneficial.
- Experience in domains such as financial services, telecom, healthcare, travel, retail, or high-tech, and familiarity with AI governance, ethics, and regulatory considerations, would
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