Salary
≈ $25k – $66k per year (Estimated)
Location
Hybrid (Bengaluru, Chennai, India)
Seniority
Staff · 7+ years exp
Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Sep 17, 2026. Ascendion scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Ascendion is an American technology services company created in 2022 when Collabera's digital engineering business was separated under private equity ownership and rebranded. It builds software, data platforms and applied artificial intelligence for enterprise clients across financial services, healthcare, retail, technology and communications, and it markets itself around engineering delivery accelerated by its own artificial intelligence tooling rather than around headcount. Headquartered in Basking Ridge, New Jersey with its largest delivery base in India, it employs several thousand engineers across North America, Europe and Asia.
Role Overview
We are hiring a Lead GenAI Engineer with 7-10 years of experience to drive the design, architecture, and delivery of enterprise-scale GenAI platforms. This role requires strong technical leadership and proven experience in building production-grade AI systems end-to-end.
Key Responsibilities
- Define architecture and technical strategy for GenAI platforms and solutions
- Lead design and implementation of complex RAG systems and agentic workflows
- Drive adoption of LangChain / LangGraph and advanced LLM orchestration frameworks
- Architect high-performance vector search and retrieval systems
- Oversee deployment strategies, including scalable cloud-native architectures
- Ensure reliability, observability, and governance of AI systems in production
- Lead and mentor engineering teams; conduct design reviews and code reviews
- Collaborate with stakeholders to align AI solutions with business goals
- Evaluate and integrate new tools, models, and frameworks in the GenAI ecosystem
Required Skills
- Expert-level proficiency in Python
- Extensive experience with RAG, LLMs, and prompt engineering at scale
- Strong expertise in LangChain / LangGraph and agent-based architectures
- Deep experience with Vector Databases and retrieval optimization
- Proven track record of deploying production-grade GenAI applications
- Strong experience with cloud (AWS/GCP/Azure), Kubernetes, and microservices architecture
- Solid understanding of system design, scalability, and distributed systems
Preferred Qualifications
- Experience leading GenAI/AI transformation initiatives
- Strong knowledge of LLMOps, MLOps, and governance frameworks
- Exposure to fine-tuning, evaluation frameworks, and guardrails
- Prior experience in client-facing or consulting roles
Common Must-Have Across All Roles
- Must have worked on at least one productionized AI/GenAI application
- Should have been involved in the end-to-end lifecycle:
- Problem definition → Data → Model → RAG → Deployment → Monitoring
- Strong ownership mindset and ability to work in fast-paced environments
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