Salary not disclosed
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Role overview
Job description
Solution Delivery & Production Deployment
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Own the hands-on delivery of AI solutions end-to-end: build, test, integrate, deploy, and ship GenAI services and agentic workflows into production.
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Take solutions from prototype to production handling deployment, release, versioning, and rollback, and keep them running reliably once they are live.
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Make sound design and trade-off decisions as you build, and bring the hard, cross-cutting calls into the team’s technical discussions contributing to the architecture, not just consuming it.
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Produce and maintain your own estimates, task breakdowns, and delivery status; surface risks, blockers, and dependencies early.
GenAI Engineering & Implementation
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Design, implement, and maintain Python-based services and workflows that integrate LLMs and GenAI capabilities with client systems and applications.
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Build agentic and multi-step workflows using orchestration frameworks and platform patterns (e.g., LangGraph, AgentCore, LangChain).
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Develop robust tooling and APIs for agents, with clear input/output schemas, error contracts, versioning, and observability hooks.
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Consume retrieval/RAG and search abstractions to improve grounding and reliability, tuning parameters (top-k, scoring, filters).
Quality, Observability & Governance
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Own the operational health of the workflows you build: monitoring, alerting, troubleshooting, and iterative improvement.
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Set up the observability and evaluation tooling for the solutions you build including tracing, logging, and metrics through an LLM observability stack (e.g., Langfuse, LangSmith), and quality, regression, and safety checks through evaluation frameworks (e.g., DeepEval, Ragas).
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Operate within established platform, security, and governance guardrails (RBAC, data access boundaries, PII handling, logging, audit) instead of building one-off mechanisms.
Collaboration & Enablement
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Partner with product managers, business stakeholders, and UX to turn problem statements and evaluation criteria into concrete, production-ready workflows.
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Participate actively in design reviews, code reviews, and architecture discussions, keeping solutions maintainable, observable, and aligned to platform standards.
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Support and guide junior engineers and consultants on the team through code review and pairing.
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Contribute to internal enablement (playbooks, examples, reusable patterns) and act as a high adopter of AI tools (e.g., Glean, Devin, Windsurf, Claude) to accelerate design, development, testing, and documentation.
Qualifications:
Why AHEAD: Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between. We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning. India Employment Benefits include: Comprehensive health insurance coverage for employees, with options to extend coverage to dependents Paid time off and company holidays, along with additional leave benefits as per policy Flexible work arrangements, supporting work-life balance Learning and development opportunities to support continuous growth and upskilling Employee wellness initiatives and programs focused on physical and mental well-being Retirement and statutory benefits in line with India regulations Inclusive and people-first culture, with a strong focus on collaboration and ownership
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About this listing
- Source: AHEAD's official careers site · still listed there on 7 Nov 2026
- Posted 21 Aug 2026
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What they are looking for
Skills & requirements
Qualification
Bachelor’s or master’s degree in computer science, Statistics, Mathematics, or a related quantitative field; Minimum of 5 years of experience in a data science-related role, with a focus on machine learning and deep learning
Department · ( Solutions Development )
Hiring company
AHEAD
AHEAD accelerates the impact of technology on clients by engineering customized data, developer, and infrastructure platforms that improve IT operations.
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