Lead technical workstreams for secure AI agents and workloads, combining advisory and engineering to design identity architectures, integrations, and production controls.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A reasonable estimate of the current range is $105,400 - $207,800. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
Lead discovery sessions to map user-to-agent-to-tool access paths
Design identity architectures and integrations for AI agents and workloads
Engineer and review token exchange, on-behalf-of access, consent, session controls
Own identity workstreams, manage dependencies and delivery milestones
Forward Deployed Engineer embedded in government client environments to deliver mission-critical solutions.
Compensation
The target base salary for this position is _____ plus commission and equity.
Responsibilities
Embed and Build: Deploy directly into clients' technical ecosystems and work with key stakeholders to understand their unique workflows, technical environments, and mission challenges.
Own the Outcome: Lead the entire technical lifecycle of strategic deployments, from discovery and architectural design to implementation and operationalization.
Be the Tip of the Spear: Serve as the primary technical authority for clients, leading workshops, debugging complex systems, and advising on platform usage.
Engineer Solutions for the Mission: Deconstruct ambiguous requirements into concrete technical solutions, architect and implement scalable data models and workflows.
Shape Our Product: Translate operational needs and feedback into the next generation of Sayari's platform.
Requirements
Bachelor's or Master's degree in a technical field
Design and build enterprise-grade, production-ready conversational and Agentic AI systems, including multi-agent, tool-augmented GenAI solutions capable of reasoning and planning.
Locations (3)
Hyderabad, Telangana, India
Noida, Uttar Pradesh, India
Chennai, Tamil Nadu, India
Responsibilities
Design, develop, and deploy production-grade GenAI solutions using advanced LLMs (OpenAI APIs such as GPT-4.1, GPT-4o, etc.).
Implement Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured enterprise data.
Design hybrid search architectures combining Vector DBs and Graph DBs.
Build Agentic AI workflows using frameworks such as LangChain, LangGraph, and Haystack.
Develop and integrate AI-powered chatbots and agents within the Azure ecosystem.
Lead the Self‑Healing Supply Chain program, shaping strategy, managing a global team, and driving AI‑enabled decision intelligence across AstraZeneca’s supply chain.
Compensation
The annual base pay for this position ranges from $177,652.80 - 266,479.20 USD. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Set the strategy: Set the SHSC vision, strategy and decision roadmap
Spearhead the program: Lead day‑to‑day program management and line‑manage the core team
Champion Decision Intelligence: Steer the Decision Architecture discipline
Deliver measurable value: Implement a governed intake, assessment and prioritization process
Leading an AI-driven supply chain transformation program focused on sensing, assessing, healing, and learning within a global biopharmaceutical context.
Compensation
The annual base pay for this position ranges from $177,652.80 - 266,479.20 USD.
Responsibilities
Set the SHSC vision, strategy, and decision roadmap
Spearhead the program by leading day-to-day program management and line-managing the core team
Chair steering committees, integrated plan reviews, and quarterly benefit reviews
Steer the Decision Architecture discipline
Implement a governed intake, assessment, and prioritization process
Lead research at the intersection of industry-scale data and academic rigor in Document Understanding, designing AI-native agentic systems to unlock insights from billions of historical and genealogical records.
Responsibilities
Innovate with State-of-the-Art AI
Architect Agentic Systems
Analyze and Optimize Multi-Modal Models
Natural Language Processing
Computer Vision
Requirements
Ph.D. in Computer Science, Data Science, Statistics, Linguistics, Engineering, or a related quantitative field
Nice to have: Strong record of academic publications in NLP, CV, or Agentic AI
Nice to have: Research in inference efficiency and optimization
Nice to have: Experience with cloud platforms and AI/ML services
Nice to have: Ability to present complex technical solutions to stakeholders
The role involves designing, building, and governing the enterprise context layer (AI, Ontology & Knowledge Graphs) to power next-generation AI, analytics, and decision intelligence solutions. It sits at the intersection of Data Engineering, Ontology Design, Knowledge Graphs, Semantic Technologies, and Agentic AI.
Responsibilities
Design semantic models, ontologies, and taxonomies
Define business entities, concepts, relationships, and hierarchies
Establish enterprise-wide semantic standards and reusable patterns
Create contextual representations of business processes and decision flows
Design and implement knowledge graphs
Requirements
Bachelor's degree in business, information systems or related discipline
Nice to have: Leadership and people management skills
Nice to have: Written and verbal communication skills
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