Knowledge Engineering Associate Director

Accenture

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Chicago, ILMilwaukee, WIDallas, TXColumbus, OHKirkland, WACincinnati, OHNew York, NYCleveland, OHOklahoma City, OKAustin, TXAlbany, NYArlington, VASt. Pete, FLHartford, CTPittsburgh, PASt. Louis, MOMiami, FLSacramento, CARaleigh, NCMinneapolis, MNMountain View, CAScottsdale, AZSan Francisco, CAMorristown, NJDenver, COBoston, MAPhiladelphia, PADes Moines, IAOverland Park, KSLos Angeles, CACharlotte, NCWalnut Creek, CACarmel, CASeattle, WAHouston, TXArlington, TXAtlanta, GAOrlando, FLRedmond, WABentonville, ARBeaverton, ORNashville, TNDetroit, MISan Diego, CA
Salary
$163,000–$434,000 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $247k
This role $298k
$130k $467k
below market most similar roles pay here above market

This role pays more than 77% of similar roles. Most pay $204,862–$289,487 — the blue band above. At the midpoint, this role pays about $298k versus about $247k for comparable roles.

Based on 240 similar postings.

Employer

About Accenture

Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.

Accenture currently has 174 open roles on FindRole.

Listed pay typically runs $94,400–$266,300 across 128 roles with salary data.

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At a glance

TL;DR · Knowledge Engineering Associate Director

The Knowledge Engineering Associate Director serves as the technical owner of Code Archaeology within the Digital Core Reinvention practice. In this role, you will lead the evidence-first discovery methodology, manage the archaeology tooling and knowledge graph pipelines, and provide public technical leadership on software architecture recovery. You will be responsible for defining engagement scopes, overseeing language-coverage roadmaps for mainframe-era languages like COBOL and PL/I, and shaping market perspectives on excavation before transformation. The position requires expertise in ontology modeling, data taxonomy, static analysis, dependency analysis, and Git history mining, alongside hands-on experience with LLM-assisted code analysis. You will solve the complex business problem of methodically excavating millions of lines of legacy code to ensure enterprise transformations are based on technical evidence rather than folklore.

What you'll do

  • Own the evidence-first discovery methodology and define the scope for archaeology engagements.
  • Defend the methodology against technical and business scope drift.
  • Manage the archaeology tooling, knowledge graph pipelines, and language-coverage roadmap.
  • Decide which assets should be standardized and productized within the portfolio.
  • Serve as the public technical voice for the discipline through conference presentations and thought leadership.
  • Lead client architecture councils to communicate the necessity of excavation before transformation.
  • Oversee the development and commercialization of productized offerings and reusable methodologies.

What we're looking for

  • Minimum of 12 years in enterprise software engineering, including significant brownfield modernization at multi-million-LOC scale.
  • Minimum of 3 years leading large-scale architectural discovery or modernization engagements as the named technical owner.
  • 5+ years of working fluency with knowledge graphs, ontology modeling, data taxonomy, static analysis, dependency analysis, and Git history mining.
  • 2+ years of hands-on work with LLM-assisted code analysis.
  • Minimum 3 years of experience leading the development, commercialization, or evolution of a productized offering, platform, or reusable methodology.
  • Bachelor's degree or equivalent (minimum 12 years) work experience; if an Associate's Degree, must have minimum 6 years work experience.
  • Published or spoken on AI-augmented code analysis, code archaeology, or software architecture recovery (preferred).

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