{"id":3293817,"url":"https://alion.io/job/pepsico-senior-manager-ai-engineering","title":"Senior Manager - AI Engineering","company":{"id":47031,"name":"Pepsico","domain":"pepsico.com","url":"https://alion.io/company/pepsico-com","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HeadHunter","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SLI/SLO/SLA","optional":false}],"status":"live","first_seen_at":"2026-10-26T20:35:08Z","employer_posted_date":null,"last_verified_at":"2026-10-26T20:35:08Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Overview\n\nAs an AI Engineer specializing in Agentic AI enablement, you will design, prototype, iterate, and productionize reusable agent capabilities that run on the enterprise AI Backbone across cloud and edge environments. You will build and harden agent behaviors (tool-use, policy constraints, memory/RAG patterns where applicable), create evaluation and regression test harnesses, and integrate agents with enterprise systems using MCP-style connectors/clients. You serve as the technical complement to the AI Solutions Lead by translating domain workflows into reliable agent components, while partnering closely with platform teams to deploy using standardized CI/CD, security, and observability patterns.\n\nResponsibilities\n\n Agent Engineering & Productionization (40%)\nPrototype, iterate, and productionize domain-aligned agent modules (plans, tool-use, task execution flows) that operate reliably within defined workflows. (Execute)\nBuild and maintain versioned agent assets (prompts, policies, tool schemas, configs) with clear change logs and reproducibility. (Execute)\nOptimize agent performance for latency and token efficiency within defined constraints (especially for edge-targeted scenarios when applicable). (Execute)\n Evaluation, Testing & Quality Signals (25%)\nImplement an AI system testing harness for assigned agents: regression suites, golden test sets (where applicable), and comparison reports for prompt/model variants. (Execute)\nMaintain evaluation metadata (test versioning, metrics, correlation IDs) to support traceability and repeatability. (Execute)\nContribute to safety/quality checks (hallucination, toxicity, policy compliance) as part of evaluation workflows defined by the program. (Execute/Consult)\n Integration with Tools and MCPs (20%)\nImplement or extend MCP clients/connectors for internal data products and approved enterprise apps using standardized interfaces, scopes, and audit patterns. (Execute)\nValidate integration behaviour with sandbox credentials, representative test data, and end-to-end workflow tests with stakeholders. (Execute/Consult)\n Operational Readiness & Collaboration (15%)\nEnsure owned components meet operational readiness expectations: logging/telemetry coverage, runbook notes, basic SLI/SLO alignment for agent health and integration reliability. (Execute/Consult)\nCollaborate with platform and transformation teams to clarify requirements, triage issues, and incorporate feedback from internal/external teams into improvements. (Execute/Consult/Informed)\nIdentify and implement small process improvements that increase repeatability (evaluation templates, prompt versioning conventions, integration test scaffolds). (Execute)\n\nDecision-Making Autonomy: Moderate — owns technical implementation for assigned agents/evals/integrations within established patterns; escalates cross-domain/security/policy decisions.\n\nSupervision Required: Moderate — receives design review and direction from L09/L10 AI leads for evaluation approach, routing standards, and sensitive integrations.\n\nComplexity of Role: High (for L08) — requires balancing quality/latency, integrating multiple enterprise tools, and ensuring reproducible evaluation under evolving requirements.\n\nCross-Functional Interactions: Yes — frequent interactions with platform, product/domain, security, SRE/observability, and enterprise app owners.\n\nQualifications\n\nKey Skills/Experience Required Minimum Qualifications:\n\nMinimum Qualifications\n\nBachelor's/Master's in CS/AI/ML/Data Science (or equivalent experience).\nHands-on experience building LLM applications (agents/tool-use/prompting) and shipping production code in Python.\n\nRequired Expertise\n\nPython engineering with production hygiene (testing, packaging, structured logging)\nAgentic AI frameworks/patterns: LangGraph/LangChain, CrewAI-style orchestration patterns; tool/function calling; prompt versioning\nEvaluation discipline: test sets, regression testing, offline eval metrics, A/B comparisons, failure taxonomy\nIntegration engineering: APIs, auth concepts, schema-based tool integration; MCP-style interface implementation preferred\nObservability basics: correlation IDs, error analysis, latency instrumentation\nCloud familiarity: enough to deploy and validate agents via platform pipelines (not owning infra)\n\nDifferentiating Competencies\n\nOwnership: takes components from prototype → tested → production-ready with clear artifacts\nProcess improvement mindset: improves repeatability and reduces rework through templates and automation\nCollaboration & customer focus: works effectively with domain teams; builds what improves real workflows\nAdaptability: adjusts quickly to changing model/tool constraints and evolving requirements\nCommunication: concise technical updates; can explain agent behaviour and evaluation results to non-experts","description_format":"text","description_chars":4834,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Soft Drinks"],"lifecycle":[{"event":"open","at":"2026-10-26T20:56:30Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":3,"expected_fill_days":36,"reasons":["seen:3","win:early"],"computed_at":"2026-10-30T05:48:23Z"},"pay":null,"html_url":"https://alion.io/job/pepsico-senior-manager-ai-engineering","json_url":"https://alion.io/job/pepsico-senior-manager-ai-engineering.json","meta":{"generated_at":"2026-10-31T02:18:33Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":3222,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":47031},"rest":"https://alion.io/mcp/rest/get_company?id=47031"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpepsico-senior-manager-ai-engineering"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpepsico-senior-manager-ai-engineering"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpepsico-senior-manager-ai-engineering"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/pepsico-senior-manager-ai-engineering\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpepsico-senior-manager-ai-engineering"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3293817}},{"tool":"search_jobs","arguments":{"company":"pepsico.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3293817},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. Docs: https://alion.io/developers"}}