{"id":1454628,"url":"https://alion.io/job/pricewaterhousecoopers-ai-solution-architect-3","title":"AI Solution Architect","company":{"id":5739,"name":"PwC","domain":"pwc.com","url":"https://alion.io/company/pwc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"C","score":69,"open_postings":2664,"ghost_share":0.509,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":62000,"max_usd":120000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":30},"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Chain-of-Thought","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Computer Use","optional":false},{"name":"Copilot","optional":false},{"name":"CrewAI","optional":false},{"name":"Cursor","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Gmail","optional":false},{"name":"Google Drive","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Mistral","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Ollama","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qwen","optional":false},{"name":"RAG","optional":false},{"name":"Slack","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"C++","optional":true},{"name":"Java","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-07-01T00:00:00Z","employer_posted_date":"2026-07-01","last_verified_at":"2026-10-28T04:46:42Z","board_verified":true,"closed_at":null,"days_open":119,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":119},"description":"Line of Service\nAssuranceIndustry/Sector\nNot ApplicableSpecialism\nRiskManagement Level\nManagerJob Description & Summary\nAt PwC, we help clients build trust and reinvent so they can turn complexity into competitive advantage. We’re a tech-forward, people-empowered network with more than 364,000 people in 136 countries and 137 territories. Across audit and assurance, tax and legal, deals and consulting, we help clients build, accelerate, and sustain momentum. Find out more at www.pwc.com.Core Responsibilities\nLead technical solutioning in client pre-sales and discovery across all sectors - translating business problems into AI architectures (RAG pipelines, agentic workflows, SDLC automation, data platforms, model risk frameworks)\n\nOwn the technical sections of client proposals and engagement scoping documents, including architecture diagrams and implementation sequencing\n\nBuild and maintain reusable accelerators and demo assets deployable within 48 hours for client workshops across all use cases\n\nLead or co-lead technical delivery on AI pilot engagements from architecture through to production handover\n\nStay current on the AI tooling landscape - with particular depth in the Anthropic/Claude ecosystem - and translate into client-relevant recommendations\n\nAdvise on AI governance and responsible AI design, particularly for FS clients subject to MAS regulatory scrutiny on model risk, explainability, and audit trails\n\nMust-Have Skills\nPython proficiency - LLM integration, API development, data engineering, and automation scripting\n\nCloud AI platforms - Azure OpenAI Service, AWS Bedrock, or GCP Vertex AI (at least one in depth)\n\nLLM orchestration - LangChain, LlamaIndex, or equivalent; multi-agent frameworks (CrewAI, AutoGen, or similar)\n\nVector databases - Pinecone, Weaviate, Chroma, pgvector, or equivalent\n\nContainerisation and CI/CD - Docker, basic Kubernetes, GitHub Actions\n\n5-14 years enterprise technology experience; minimum 2 years in production AI delivery\n\nAnthropic / Claude Ecosystem - Strongly Preferred\nGiven the practice's primary AI platform orientation, depth in the Anthropic/Claude ecosystem is a material differentiator. Candidates with hands-on production experience across multiple Claude capabilities will be prioritised.\nClaude API - tool use, computer use, vision, and document processing in production applications\n\nClaude Code - agentic coding workflows, CLI integration, MCP server configuration, and multi-agent software development pipelines\n\nClaude claude.ai and Projects - enterprise deployment patterns, system prompt design, memory and context management\n\nAnthropic prompt engineering - chain-of-thought elicitation, XML-structured outputs, multi-turn conversation design, and retrieval-augmented prompting\n\nClaude model family knowledge - Opus, Sonnet, Haiku trade-offs for latency, cost, and capability in production architectures\n\nMCP (Model Context Protocol) - server implementation, tool registration, and integration with enterprise data sources (Google Drive, Gmail, Slack, CRMs)\n\nAnthropic API batch processing, streaming, and rate limit management for enterprise-scale 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