{"id":1284927,"url":"https://alion.io/job/success-pact-consulting-applied-ai-engineer","title":"Applied AI Engineer","company":{"id":3806412,"name":"Success Pact Consulting","domain":"successpact.com","url":"https://alion.io/company/success-pact-consulting","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":51000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":31},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic 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Codex","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"Prefect","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-08-19T04:23:36Z","employer_posted_date":null,"last_verified_at":"2026-08-19T04:23:36Z","board_verified":false,"closed_at":null,"days_open":67,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":67},"description":"Responsibilities:\n\n- AI-Powered Feature Development: Build LLM-powered features directly into client-facing platforms, including research intelligence tools, natural language query layers, automated summarisation, and agentic workflows that fundamentally change how investment teams work.\n\n- Agentic Tooling and MCP Integration: Design and implement MCP-connected data sources, agentic pipelines, and AI orchestration layers using frameworks like Claude Code, LangGraph, Open Claw, Open Code and similar, extending client platforms with live, intelligent data access.\n\n- Full-Stack Application Development: Build end-to-end applications tailored to each client's unique portfolio analytics, risk management, and research workflows from backend APIs to responsive frontends.\n\n- Backend Services: Design and maintain high-performance APIs using Python (FastAPI or similar) that power client-specific data access, analytics, and AI inference.\n\n- Frontend Development: Build intuitive, responsive user interfaces in React that enable investment teams to interact with complex financial data clearly and efficiently.\n\n- Data Pipeline Development: Build and maintain ETL pipelines that handle critical financial market data- positions, securities, risk metrics, and research signals with reliability and performance.\n\n- Financial Analytics: Implement analytics layers for performance and risk calculations using time series and linear algebra operations (Pandas, Polars).\n\n- Ship Fast, Iterate Often: Deliver working software in compressed timelines, gather direct feedback from hedge fund users, and continuously improve, treating speed and quality as complementary, not competing.\n\n- Kubernetes Deployments: Be able to work fluidly with Kubernetes within each client environment to be able to ship fast and reliably.\n\nRequirements:\n\n- 3+ years of software engineering experience spanning both backend and frontend development.\n\n- Fundamental understanding of the agentic loop that is used within most agent frameworks such as Codex, Claude Code, Open Code, Cline, etc.\n\n- Strong Python skills with hands-on experience building APIs using FastAPI, Flask, or Django as well as CLIs with click, argparse, etc.\n\n- Frontend development experience with modern frameworks, particularly React.\n\n- Solid understanding of RESTful APIs, data modelling, and secure API design.\n\n- Experience with SQL and analytical libraries (Polars, Pandas) for computational workloads.\n\n- Exposure to cloud platforms (Azure, AWS, or GCP) and cloud-native architectures.\n\n- Experience with containerised development (Docker) and deployment workflows.\n\n- Passion for AI: Genuine conviction that AI is transforming software, demonstrated through active use of AI tools in your development workflow (Claude, GitHub Copilot, Cursor, or similar) and curiosity about what comes next.\n\n- Deep interest in finance: Strong desire to understand how institutional investors, hedge funds, and asset managers think, make decisions, and use technology; you find the domain genuinely compelling, not just a backdrop.\n\n- Excellent communication skills and comfort translating technical concepts to non-technical stakeholders.\n\n- Strong problem-solving instincts and comfort operating with ambiguity.\n\n- 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