1 day ago
Remote, IndiaSenior
Responsibilities
- Diagnose customer business challenges, map data landscapes, and co-design AI solutions.
- Lead end-to-end design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision applications.
- Prototype and deliver proofs of concept, then own scoping, architecture, development, deployment, and post-launch optimization.
- Build enterprise AI applications, scalable data pipelines, integrations, dashboards, and multi-agent workflows.
- Deploy and operate solutions using full-stack engineering, DevOps, GPU infrastructure, observability, monitoring, and telemetry.
- Collaborate with sales and customer success to identify expansion opportunities and high-value use cases.
- Feed field insights to Platform Engineering and Product teams and create reusable architectures, accelerators, and frameworks.
- Mentor engineers and customer teams through knowledge transfer and AI capability development.
Requirements
- Palantir certification is required.
- At least 5 years of experience in software engineering, data engineering, or AI/ML delivery, including at least 4 years in customer-facing or field roles.
- Proven experience building and deploying enterprise-scale AI/ML applications in production.
- Deep proficiency with Python and experience with Node.js or Go, React or Vue, and SQL or NoSQL databases.
- Hands-on experience with LLMs, prompt engineering, vector databases, data pipelines, dashboards, RAG, and agent orchestration frameworks.
- Strong Docker, Kubernetes, CI/CD, GPU infrastructure, and cloud-native deployment skills.
- Experience integrating ERP systems, data warehouses, data lakes, streaming architectures, and other heterogeneous enterprise systems.
- Experience with Palantir Foundry, AIP, ontology modeling, Uniphore BAIC, or similar enterprise AI platforms.
- Knowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.
- Experience with multi-agent systems, tool use, autonomous workflow orchestration, knowledge graphs, semantic modeling, and ontology-driven data management.
- Familiarity with NVIDIA H100 or B200 GPUs, InfiniBand, OpenStack, and VMware.
- Strong ability to translate ambiguous customer needs into engineering plans and communicate with executives and cross-functional teams.
- Prior technology consulting, AI startup, Forward Deployed, or Solutions Engineering experience and domain expertise in listed regulated or industrial sectors are relevant qualifications.
Benefits
- The role is embedded directly with strategic enterprise customers and may involve on-site customer work.
- The position offers autonomy and end-to-end ownership backed by the scale and resources of a global technology company.
- Rackspace Technology states that it provides equal employment opportunity and disability or special-needs accommodations.
- The role includes exposure to high-impact enterprise AI projects and opportunities to mentor teams and build reusable internal capabilities.
About Rackspace
Rackspace provides managed cloud and IT services for enterprises, including multicloud operations, cloud migration, private cloud, managed security, and application/platform management across AWS, Azure, Google Cloud, and VMware. It operates a services-led business model with consulting and ongoing management for regulated and mission‑critical workloads, including healthcare. Founded in 1998 and headquartered in San Antonio, Texas, Rackspace is majority‑owned by Apollo Global Management.