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This role is for one of our clients
Industry: Software Development
Seniority level: Mid-Senior level
Min Experience: 6 years
Location: Bengaluru
JobType: full-time
We are hiring a Principal AI Solutions Engineer to work directly with enterprise customers to design, deploy, and scale production-grade AI systems. This is a deeply hands-on, high-impact role for engineers who enjoy building real systems in real environments—not demos or experiments.
You will operate at the frontline of customer adoption, translating complex business problems into secure, explainable, and scalable AI architectures. Acting as both a technical lead and trusted advisor, you will bridge the gap between advanced AI capabilities and enterprise operational reality.
This role is ideal for engineers who enjoy autonomy, ambiguity, and direct ownership of outcomes.
Key Responsibilities
Enterprise AI Deployment & Ownership
Own end-to-end delivery of AI solutions from initial scoping to live production rollout.
Write and maintain core application, integration, and orchestration code for customer deployments.
Ensure AI systems meet enterprise standards for reliability, scalability, and security.
Diagnose and resolve complex system issues across data, model, and infrastructure layers.
Intelligent Systems & Agent Architecture
Design and implement AI-powered systems including LLM-driven workflows, autonomous agents, and retrieval-based reasoning layers.
Build tailored architectures using modern AI frameworks and orchestration tools.
Adapt solutions to customer-specific data landscapes, constraints, and compliance requirements.
Data & Platform Engineering
Architect and manage end-to-end data flows across ingestion, transformation, storage, and serving layers.
Integrate with modern data platforms and streaming systems to support high-throughput, low-latency AI workloads.
Ensure data integrity, lineage, and explainability across AI pipelines.
Rapid Prototyping & Production Scaling
Deliver fast, high-quality proofs-of-concept that validate business value early.
Convert MVPs into hardened, production-grade systems without sacrificing speed.
Balance experimentation with operational rigor.
Customer Partnership & Technical Leadership
Work shoulder-to-shoulder with customer engineering, data, and product teams.
Lead architectural discussions and guide customers toward best-practice AI implementations.
Serve as a conduit between customer needs and internal product direction.
AI Governance, Observability & Trust
Help customers operationalize AI responsibly through monitoring, explainability, drift detection, and governance practices.
Embed transparency and accountability into AI system design.
Support enterprise readiness for audits, compliance, and long-term maintainability.
Enablement & Knowledge Sharing
Uplift customer teams through hands-on guidance, reviews, and mentoring.
Set a high bar for engineering quality, documentation, and operational excellence.
Contribute learnings back into internal playbooks and product improvements.
Ideal Candidate Profile
Must-Have Experience
5+ years building and deploying production-grade AI, ML, or data-intensive systems.
Strong computer science fundamentals with systems-level thinking.
Advanced proficiency in Python, JavaScript, or Java, with a focus on backend and distributed systems.
Hands-on experience working with LLM-based systems, intelligent agents, or generative AI workflows.
Deep understanding of enterprise data architectures, integrations, and pipelines.
Proven success in customer-facing or solutions engineering roles.
Ability to communicate complex technical ideas in a clear, outcome-oriented way.
Comfort operating in fast-moving, ambiguous environments with high ownership.
Work Setup
Hybrid role based in Bengaluru (2 days per week in office).
Willingness to travel up to 25% for on-site customer engagements.
Nice to Have
Experience with AI observability, monitoring, or model governance platforms.
Exposure to Kubernetes, cloud infrastructure (AWS, GCP, Azure), or MLOps tooling.
Hands-on experience deploying conversational or agentic AI in enterprise contexts.
Familiarity with explainability, bias detection, or responsible AI frameworks.
Open-source contributions in AI, data, or platform engineering.
What This Role Offers
Direct ownership of enterprise AI outcomes—not just features.
Exposure to complex, high-stakes production environments.
Opportunity to shape both customer success and internal product evolution.
A role at the intersection of advanced AI, real-world systems, and business impact.
Core Skills
Enterprise AI Deployment · Solutions Engineering · LLMs & Agentic Systems · Data Engineering · AI Observability · Responsible AI · Customer-Facing Engineering · Distributed Systems · Python / JavaScript / Java
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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