Conversational AI Engineering Manager
Quick Summary
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Conversational AI Engineering Manager based in India.
This fully remote leadership role offers the opportunity to shape engineering teams and deliver production-grade conversational AI solutions at scale.
You will lead engineers across multiple experience levels while establishing strong practices around development, testing, documentation, and continuous improvement.
The role combines people leadership, technical direction, delivery ownership, and close collaboration with product teams, clients, and business stakeholders.
You will oversee conversational AI implementations spanning chat and voice bots, routing, integrations, and knowledge-driven experiences.
The position also requires a strong focus on NLU, LLM prompting, conversational design, evaluation, monitoring, reliability, and safe human handoffs.
You will help translate complex business requirements into structured technical plans, measurable milestones, and reliable production solutions.
This is an opportunity for an experienced engineering leader to influence both technical strategy and team development within a fast-moving global environment.
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Lead, manage, and coach engineers across multiple levels, supporting onboarding, performance management, career development, and promotion readiness.
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Build a high-trust engineering culture centered on effective feedback, code reviews, testing, documentation, and learning from incidents.
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Recruit and hire engineering talent across different levels while supporting responsible team growth.
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Own delivery outcomes across concurrent projects, including planning, prioritization, scope management, dependency coordination, and risk mitigation.
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Partner with Product, clients, and other stakeholders to translate business requirements into clear technical plans, milestones, and measurable outcomes.
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Lead client interactions and stakeholder management throughout project planning and delivery.
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Create and review business and technical documentation, including BRDs, PRDs, FRDs, SOWs, and NFRDs.
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Document AI solutions through use cases, workflows, integrations, and AI-specific product and business requirements.
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Establish and continuously improve agile operating practices, including sprint or Kanban workflows, roadmaps, retrospectives, and engineering metrics.
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Establish and enforce CI/CD workflows across development environments, including workflows with and without source-code repositories.
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Lead implementation and enhancement of conversational AI solutions using platforms such as Cognigy and/or Amazon Lex with Amazon Q.
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Oversee conversational AI capabilities including chat and voice bots, routing, integrations, and knowledge-driven experiences.
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Establish best practices for conversational design, NLU and LLM implementation, prompt and tooling hygiene, and safe fallback or live-agent handoff mechanisms.
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Improve bot quality through structured evaluation, testing strategies, monitoring, and continuous optimization.
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Define and enforce standards for reliability, observability, logging, dashboards, alerting, service-level objectives, and on-call readiness.
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Lead incident response and root-cause analysis while ensuring lessons learned result in sustainable engineering improvements.
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Collaborate with security and compliance stakeholders on customer data handling, retention, access controls, and related requirements.
Requirements
~2 min read-
Proven experience in engineering management, technical leadership, or a similar software engineering leadership role.
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Demonstrated experience managing and developing engineers across multiple levels and building high-performing technical teams.
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Strong experience delivering conversational AI solutions, including chat and/or voice bots, routing, integrations, and knowledge-based experiences.
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Hands-on experience with platforms such as Cognigy, Amazon Lex, Amazon Q, or comparable conversational AI technologies.
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Strong understanding of conversational design, NLU, LLM prompting, AI tooling, evaluation methodologies, and safe fallback mechanisms.
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Experience translating business requirements into technical solutions, delivery plans, milestones, and measurable outcomes.
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Strong client-facing and stakeholder-management capabilities, with confidence communicating technical concepts to both technical and non-technical audiences.
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Experience creating and reviewing BRDs, PRDs, FRDs, SOWs, NFRDs, and AI-specific technical documentation.
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Strong understanding of agile delivery methodologies, including Scrum or Kanban, roadmapping, retrospectives, and engineering metrics.
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Experience establishing or enforcing CI/CD practices and modern software delivery workflows.
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Knowledge of software engineering fundamentals, including code review, automated testing, documentation, observability, and production reliability.
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Experience with incident management, root-cause analysis, SLOs, monitoring, logging, dashboards, and alerting.
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Ability to collaborate effectively with Product, Engineering, clients, security, compliance, and other cross-functional stakeholders.
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Strong organizational, problem-solving, communication, and decision-making skills.
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Ability to operate effectively in a remote, fast-paced, globally distributed environment.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- September 29, 2026
Signal breakdown
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